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Data Analytics Director, Business Intelligence & Analytics (BIA) - USA Remote at Turnitin

Director leads business intelligence strategy, defines KPIs and metrics, owns revenue operations analytics foundation, and modernizes data stack across the organization.

Lead Remote Posted about 4 hours ago RemoteFirstJobs Product
What this role involves

Company Description

When you join Turnitin, you’ll be welcomed into a company that is a recognized innovator in global education. For over 25 years, Turnitin has partnered with educators and institutions to develop learning integrity solutions that recognize the enduring value of critical thinking in a rapidly changing world. Over 16,000 academic institutions, publishers, and corporations use our services in more than 185 countries around the world: Turnitin Feedback Studio, Clarity, Originality, Gradescope, ExamSoft, Similarity, and iThenticate. Protecting the value of an authentic education is at the heart of who we are.

Experience a remote-first culture that empowers you to work with purpose and accountability in a way that best suits you, supported by a comprehensive package that prioritizes your overall well-being. Our diverse community of colleagues are all unified by a shared desire to make a difference in education.

Turnitin is a global organization with team members in over 35 countries including the United States, Mexico, United Kingdom, Australia, Japan, India, and the Philippines.

Job Description

We are seeking a Director, Business Intelligence & Analytics (BIA) to report to the Vice President of Revenue Operations. This is a builder’s role for a leader who thinks in systems, treats analytics like a product, and is excited to operate at the frontier of AI-augmented decision-making. A leader who can define what we measure, why it matters, and how every number ties back to a clean, trusted source. Before anything else, this person establishes the foundation the rest of the business runs on: a rigorous set of KPIs, unambiguous metric definitions, sound data models, and a single version of the truth that executives and sellers alike can rely on. Get that right, and everything else compounds. Get it wrong, and no tool or technique can save it.

You will own the operational backbone of Revenue Operations analytics — the metrics, the definitions, the governance, and the reporting that leadership uses to run the business. You will gather requirements across teams, reconcile conflicting numbers, close data gaps, and turn fuzzy questions into precise, durable measures. This is the work that makes everything else possible.

With that foundation in place, you will modernize how we deliver it. We are migrating from a legacy Redshift/Alteryx/Tableau stack to a modern, code-driven ecosystem built on Redshift, dbt, Dagster, and Airbyte, paired with a next-generation, version-controlled BI layer. The goal is to treat analytics like a well-engineered software product — tested, documented, version-controlled, and built to scale as fast as the business does.

This modernization unlocks the next chapter: an AI-augmented function where a strong operational core is amplified by emerging tooling. We believe the analytics team of the next few years will increasingly work from an AI coding cockpit — agentic developer tools like Claude Code and Codex alongside GitHub — to build, review, and ship pipelines, models, and dashboards. On top of well-defined metrics, that opens the door to conversational analytics, AI-generated narratives, and agents that surface and act on insight. The key word is on top of — AI multiplies a solid foundation; it does not substitute for one. The ideal candidate has already moved past the chat window and uses agentic coding assistants to do real engineering work, but reaches for them in service of operational rigor, not in place of it.

As the subject matter expert for Business Intelligence and Analytics, you will partner closely with field and operational teams, instituting leading practices that pair analytics-engineering discipline (Git, CI/CD, testing, semantic layers) with self-service access. You will lead a team of Business Intelligence & Analytics Analysts, Analytics/Data Engineers, and Data Quality Specialists.

Above all, this is a full-stack, player-coach role — not a hands-off manager. You’ll lead a team, but you’ll also be in the work: your morning might be deep in data engineering, pairing with Claude Code to refactor a dbt model or debug a Dagster pipeline, and your afternoon might be building and delivering a polished, board-ready presentation that translates that same data into a clear story for the C-suite. We’re looking for someone who is equally credible in a terminal and in the boardroom, and who is genuinely energized by the full range — from the plumbing to the podium.

Key Responsibilities:

Operational Excellence & Metric Definition (the foundation)

  • Own and maintain a comprehensive, well-governed set of business KPIs and the precise metric definitions behind them — the trusted source the rest of the business runs on. This spans the core recurring-revenue metrics this function lives and dies by — ARR, ACV, GRR, NRR, churn and contraction, bookings, pipeline and pipeline coverage, win rate, sales-cycle length, quota attainment, and forecast accuracy — along with the upstream operational measures that feed them.
  • Nail the definitions where the traps live: how contraction is treated across GRR vs. NRR, churn vs. downgrade, ACV vs. TCV, new vs. expansion vs. renewal, and how each metric is segmented and rolled up. Make the calculation logic explicit, documented, and consistent everywhere it appears.
  • Establish a “single version of the truth”: reconcile conflicting numbers, eliminate ambiguity in how metrics are calculated, and ensure every figure traces back to a clean, documented source.
  • Gather requirements across teams, identify and close data gaps, and turn fuzzy business questions into durable, precise measures.
  • Design and document the analytics/data model for key personas across Turnitin — sellers, sales management, executives, and operations staff.
  • Audit and ensure the cleanliness, completeness, and reliability of data through automated testing and validation.
  • Partner with the Business Planning & Operations group to co-develop and continuously improve reporting and analysis, including preparation for Quarterly Business Reviews.
  • Build automated, repeatable reporting solutions rather than one-off manual reports.

Strategic Leadership

  • Develop and execute a BI strategy aligned with company objectives, anchored in operational rigor and trusted metrics, and built to scale with business growth.
  • Establish the architecture, standards, and governance that keep data trustworthy as the function and the business scale.
  • Shape the long-term vision for the analytics function and the roadmap that takes the team from today’s stack to a modern, code-driven, and ultimately AI-augmented operating model.
  • Provide thought leadership and drive innovation across the enterprise analytics portfolio.

Modern Data Platform & BI-as-Code (how we deliver the foundation)

  • Lead the migration from the legacy stack (Redshift, Alteryx, Tableau) to a modern ecosystem: dbt for transformation and modeling, Dagster for orchestration, Airbyte for ingestion, Redshift as the warehouse, and a modern code-first BI/semantic layer.
  • Treat BI as a software product — version control everything in Git, with code review, testing, CI/CD, and documentation as the default way of working.
  • Stand up and govern a code-driven semantic layer that turns the metric definitions above into reusable, testable, single-source assets, replacing brittle GUI-built reporting.
  • Drive data quality, governance, security, and access controls as code, with automated validation and monitoring.
  • Develop intuitive self-service dashboards that support global requirements.

AI & Agentic Analytics (the amplifier, built on the foundation)

  • Champion the adoption of agentic coding tools (e.g., Claude Code, Codex) across the team for pipeline development, model building, dashboarding, and analysis — moving well beyond chat-window prompting.
  • Build conversational analytics experiences that let stakeholders query data in natural language and receive trustworthy, governed answers — only ever on top of well-defined metrics.
  • Implement AI-generated narratives that automatically explain “what happened and why” on top of dashboards and KPIs.
  • Pilot and operationalize AI agents that don’t just surface insight but take action on it — drafting analyses, opening pull requests, flagging anomalies, and proposing next steps.
  • Stay ahead of the rapidly evolving LLM and agent tooling landscape, and translate it into practical productivity gains for Revenue Operations.

Collaboration and Communication

  • Work closely with business users, stakeholders, and the broader Go-To-Market and Revenue Operations teams to translate business needs into analytics initiatives.
  • Communicate effectively across technical and non-technical audiences and across geographies.
  • Present complex analyses and insights to non-technical stakeholders in a clear, actionable manner.

Team Development

  • Lead as a player-coach — set direction and mentor the team, while staying hands-on in the build, modeling the engineering and presentation standards you expect.
  • Build, mentor, and manage a high-performing team of analysts, analytics/data engineers, and BI developers.
  • Upskill the team in analytics engineering practices and AI-assisted development.
  • Foster a culture of innovation, continuous improvement, and data-driven decision-making.

Qualifications

Basic Qualifications

Experience

  • Minimum of 10 years in business intelligence, data analytics, analytics engineering, or related fields, with at least 5 years in a leadership role.
  • 7+ years across business/revenue operations, business analytics, consulting, and/or information technology.
  • Demonstrated track record defining KPIs and metric frameworks, and establishing a trusted single source of truth across an organization.
  • Deep fluency in SaaS recurring-revenue metrics — ARR, ACV, GRR, NRR, churn/contraction, bookings, pipeline, win rate, quota attainment, and forecast accuracy — including the judgment to define them rigorously and defend the calculation logic.
  • Proven ability to source and integrate data from multiple systems into a single, trusted view, and to reconcile conflicting numbers.
  • Practical end-to-end experience across requirements, design, development, testing, and deployment of analytics solutions at varying scale.
  • Strong SQL skills, plus working proficiency in Python for data work and automation.
  • Experience with BI and visualization tools (e.g., Tableau today, with a clear point of view on code-first BI tools) and with CRM data for revenue reporting and forecasting (e.g., Salesforce).
  • Proven track record implementing and managing self-service BI solutions.
  • Experience analyzing complex data relationships and exploring “what-if” scenarios.
  • Hands-on experience with a modern, code-driven data stack — including transformation (dbt), orchestration (Dagster or similar), and ingestion/ELT (Airbyte or similar) — on a cloud warehouse such as Redshift.
  • Comfort working in a version-controlled, code-first environment (Git/GitHub), including code review and CI/CD for analytics.
  • Demonstrated, hands-on use of LLMs and agentic coding tools (e.g., Claude Code, Codex) for real engineering and analytics work — not just chat-based prompting.

Skills

  • A systems thinker — able to see how metrics, data sources, processes, and teams connect, and to design analytics that hold together as the whole system changes.
  • Strong analytical skills — able to evaluate information from multiple sources, reconcile conflicts, decompose high-level requests into detail, and abstract detail into general understanding.
  • Demonstrated business acumen and the ability to apply technology to solve business problems.
  • Self-starter who operates independently with a track record of success on strategic and operational work.
  • Ability to lead teams across functions and geographies on ambiguous, complex problems.
  • A full-stack player-coach — hands-on enough to build the pipeline yourself, polished enough to present the result to the C-suite, and able to move between the two in the same day.
  • Strong written and verbal communication skills, with a track record of presenting to senior management.
  • Ability to manage multiple competing priorities and drive projects to completion.
  • Sound business judgment, a proven ability to influence, and a bias for ownership.

Education

  • Bachelor’s degree in Business, Data Science, Computer Science, or a related field. A Master’s degree or MBA is preferred.

Preferred Qualifications

  • Experience supporting education and/or nonprofit institutions.
  • Management or Financial Consulting background.
  • Experience building conversational analytics, AI-generated narratives, or semantic/metrics layers.
  • Experience deploying AI agents that build pipelines, dashboards, or analyses, or that act on insights.
  • Familiarity with data quality and observability tooling, and with governance-as-code.
  • Advanced degrees, certifications, or coursework in business intelligence, analytics, data science, or AI/ML.

Additional Information

The expected annual base salary range for this position is: $130,350/year to $217,250/year. This position is bonus eligible.

Actual compensation will be provided in writing at the time of offer, if extended, and is determined by work location and a range of other relevant factors, including but not limited to: experience, skills, degrees, licensures, certifications, and other job-related factors. Internal equity, market and organizational factors are also considered.

Total Rewards @ Turnitin

At Turnitin, we believe Total Rewards go far beyond pay. While salary, bonus, or commission are important, they’re only part of the value you receive in exchange for your work.

Beyond compensation, you’ll experience the intrinsic rewards of unleashing your potential and making a positive impact on global education. You’ll also thrive in a culture free of politics, surrounded by humble, inclusive, and collaborative teammates.

In addition, our extrinsic rewards include generous time off and health and wellness programs that provide choice, flexibility, and a safety net for life’s challenges. You’ll also enjoy a remote-first culture that empowers you to work with purpose and accountability in the way that suits you best, all supported by a comprehensive package that prioritizes your overall well-being.

Our Mission is to ensure the integrity of global education and meaningfully improve learning outcomes.

Our Values underpin everything we do.

  • Customer Centric: Our mission is focused on improving learning outcomes; we do this by putting educators and learners at the center of everything we do.
  • Passion for Learning: We are committed to our own learning and growth internally. And we support education and learning around the globe.
  • Integrity: Integrity is the heartbeat of Turnitin—it is the core of our products, the way we treat each other, and how we work with our customers and vendors.
  • Action & Ownership: We have a bias for action. We act like owners. We are willing to change even when it’s hard.
  • One Team: We strive to break down silos, collaborate effectively, and celebrate each others’ successes.
  • Global Mindset: We consider different perspectives and celebrate diversity. We are one team. The work we do has an impact on the world.

Global Benefits

  • Remote First Culture
  • Health Care Coverage
  • Education Reimbursement*Competitive Paid Time Off
  • Self-Care Days
  • National Holidays
  • 2 Founder Days + Juneteenth Observed
  • Paid Volunteer Time Off
  • Charitable Contribution Match
  • Monthly Wellness or Home Office Reimbursement
  • Access to Employee Assistance Program (mental health platform)
  • Parental Leave
  • Retirement Plan with match/contribution

Seeing Beyond the Job Ad

At Turnitin, we recognize it’s unrealistic for candidates to fulfill 100% of the criteria in a job ad.  We encourage you to apply if you meet the majority of the requirements because we know that skills evolve over time. If you’re willing to learn and unleash your potential alongside us, join our team!

Turnitin, LLC is an Equal Opportunity Employer- vets/disabled.

#LI-LL1

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Data Analytics Principal, Marketing Analytics

Leads marketing analytics initiatives, analyzing campaign performance and business metrics to drive data-informed marketing strategies.

Lead Posted 1 day ago Jobicy AI
What this role involves
About Remote Remote is solving modern organizations’ biggest challenge – navigating global employment compliantly with ease. We make it possible for businesses of all sizes to recruit, pay, and manage...
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Data Analytics Director, Marketing Analytics

Leads and scales the marketing analytics function, setting strategy and managing analytics initiatives to support company growth.

Lead Posted 2 days ago Jobicy AI
What this role involves
About the roleChime is looking for a Director of Marketing Analytics to lead and scale our Marketing Analytics function during a critical phase of growth. In this role, you’ll set...
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Data Analytics Data Platform Architect at TailorCare

Lead the design and strategy of an end-to-end healthcare data platform that ingests, resolves, and acts on patient data in real-time while ensuring HIPAA compliance and AI governance.

Lead Hybrid Posted 4 days ago RemoteFirstJobs Product
What this role involves

About the Role

TailorCare is a value-based musculoskeletal (MSK) care platform combining clinical expertise, digital tools, and a yield-based operating model. We are now operationalizing Operating Model 3.0, a shift from uniform delivery to yield-based alignment, in which every patient receives investment proportional to a real-time Yield Score (Probability × Value × Addressability), and an ROI Gate continuously calibrates Wallet (financial investment) and Muscle (operational intensity).

This requires a data and AI platform that ingests, resolves, scores, decides, and acts in minutes, with the explainability and governance healthcare demands. You will lead that build: set the strategy, design the data platform, drive vendor decisions, and partner with engineering, product, clinical, and operations leadership to deliver it. This is a hybrid strategy-and-architecture role; you will move comfortably from a CTO whiteboard conversation to an EDI 837 parser to a model-evaluation review without losing the thread.

Primary Responsibilities

  • Set strategy. Own the multi-year data strategy supporting Operating Model optimization and TailorCare’s extension beyond MSK; frame tradeoffs for the executive team; protect strategic data moats (canonical patient and provider graphs, proprietary outcome labels, and contribute to yield-calibrated decisioning IP)
  • Architect the platform end-to-end. Ingestion, event bus, identity resolution, lakehouse, feature store, ROI Gate decisioning, action orchestration, observability. Define the event taxonomy, schema registry, and data contracts that govern how every source flows in
  • Lead vendor strategy. Evaluate and select across clearinghouses, clinical networks, claims systems, provider intelligence, conversational AI, CDPs, and more, negotiating export rights, schema stability, and contribute to defining BAA scope. Build payer-neutral patterns from day one
  • Set the bar for HIPAA, PHI, and AI governance. Classification at ingestion, field-level access controls, infrastructure-level scrubbing, vendor data governance, training-data lineage, and consent chains.
  • Partner across functions. Translate architecture into staffed delivery with each engineering team; collaborate with clinical leadership on Patient Reported Outcome, extraction accuracy, and outcome labels; work with operations to make the intake and data aggregation meaningful.
  • Other duties as assigned

Qualifications

  • 10+ years working with healthcare data, including 4+ years in architecture or strategy leadership
  • Deep hands-on knowledge of healthcare data: X12 EDI (270/271/276/277/278/834/835/837), FHIR R4, HL7 v2 (especially ADT), CCD/C-CDA, NCPDP, and the realities of integrating with payers, EHRs, clearinghouses, and HIEs
  • Experience working with AI team developing predictive models and ability to act as the liaison between AI modeling and data platform.
  • Proven track record designing production data platforms at scale, streaming and batch, with managed Kafka or equivalent, lakehouse architectures (Snowflake / Databricks / BigQuery), dbt-style orchestration, modern observability
  • Solid grounding in ML/AI systems: feature stores, point-in-time correctness, model lifecycle, NLP for clinical text. You evaluate model proposals on their merits
  • Direct experience with patient identity resolution (deterministic + probabilistic) and tokenization (Datavant or equivalent)
  • Working knowledge of value-based care economics: MLR, attribution, episode costing, risk adjustment, and how reimbursement models shape data requirements
  • Demonstrated executive presence: framing tradeoffs, defending recommendations, adjusting when wrong, staying technically credible
  • HIPAA-fluent. You engineer PHI minimization, BAA structures, and audit requirements as first-class concerns
  • Ability and willingness to travel up to 10% as needed for onsite meetings, team collaboration, and company events.

Preferred Qualifications

  • Hands-on experience with at least one major longitudinal claims dataset (Komodo, Truveta, HealthVerity, Optum, IQVIA) and integration
  • Highly collaborative and experienced with a broad range of business holders
  • Experience integrating clinical data networks
  • Experience with conversational AI in a contact-center context (Cresta, Observe.AI, or built in-house)
  • Multi-payer scale experience
  • Early-stage / scaling startup background, comfort with ambiguity and the ability to make calls without perfect information

What you will deliver in year one

  • Be a key leader in driving build vs. buy data acquisition decisions
  • Canonical patient master service in production; ≥95% deterministic match rate, documented probabilistic strategy
  • Real-time event bus with ≥10 production event types, SLO dashboards, and downstream consumers live
  • Real-time ADT, eligibility (270⁄271) and prior-auth (278) integrations live with sub-second response
  • Salesforce (TailorCare-captured) clinical operational data fully instrumented
  • Clinical data network integration (Health Gorilla or Particle) with NLP extraction on radiology and specialist notes
  • ROI Gate v1 deployed, routing ≥80% of newly-identified patients; closed-loop attribution from marketing to outcome operational

What’s In It For You

  • Meaningful Work: We are dedicated to our mission and deeply value our patients and each other. Each day offers the opportunity to make a positive impact.
  • Work Environment: We operate as a remote-first company with options for a hybrid work model in Nashville.
  • Time Off: Our generous paid time off (PTO) and holiday plans ensure you have ample time to rest and recharge.
  • Family First: We offer paid parental leave and support a healthy work-life balance, encouraging flexibility and autonomy. We love talking about our family and pets!
  • Comprehensive Benefits: From Day 1, employees enjoy medical, dental, vision, life, and disability insurance, wellness resources and an employer HSA contribution.
  • Fair Compensation: We are committed to equitable pay for all team members and support your future goals with a 401k plan that includes employer matching.
  • Community: We foster an inclusive environment where you can rely on your teammates, share honest feedback, and feel comfortable being your authentic self at work each day.

TailorCare seeks to recruit and retain staff from diverse backgrounds and encourages qualified candidates to apply. TailorCare is an equal opportunity employer and does not discriminate on the basis of age, sex, gender identity/expression, sexual orientation, color, race, creed, national origin, ancestry, religion, marital status, political belief, physical or mental disability, pregnancy, military, or veteran status.

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Data Analytics Senior Staff Data Scientist at Reddit, Inc.

Senior technical leader who defines relevance metrics, evaluation frameworks, and analytical strategies for Reddit's content ranking and recommendation systems.

Lead Posted 4 days ago RemoteFirstJobs Product
What this role involves

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet.

Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes.

Reddit’s relevance challenges are uniquely complex. Our platform is a deeply interconnected network of communities, contributors, and consumers - where the notion of “relevance” spans personalized content ranking, community discovery, and search across an enormous corpus of authentic, user-generated content. We need a senior technical leader who thrives on these hard problems and can raise the bar for how we measure, evaluate, and improve the quality of recommendations and search results across the entire Consumer organization.

As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on relevance measurement and evaluation, partnering closely with Feeds and Search ML teams to tackle the most complex ranking, recommendation, and retrieval challenges across Consumer. You will shape how Reddit understands content quality, define the metrics and analytical frameworks that guide relevance improvements, and influence product strategy through rigorous analysis and experimentation.

Responsibilities

  • Serve as the technical authority on relevance metrics and evaluation methodology across Consumer, setting standards for how we measure the quality of feeds, search results, and recommendations in a complex, community-driven environment
  • Develop metrics frameworks and offline evaluation approaches for ranking and recommendation systems, including proxy metrics that reliably predict long-term outcomes like retention, community health, and user satisfaction
  • Design and analyze experiments for relevance features, accounting for challenges unique to networked platforms such as spillover effects between communities, interference between contributors and consumers, and long-run impacts of ranking changes on content supply
  • Identify opportunities where improved measurement and analysis can unlock product insights that were previously unmeasurable or ambiguous, particularly around content quality, search intent understanding, and personalization effectiveness
  • Partner deeply with ML engineers and product teams to translate model performance metrics into user-facing impact
  • Influence the long-term product strategy for Feeds and Search by synthesizing insights from experimentation, observational analysis, and metric deep-dives into clear, actionable recommendations for senior leadership
  • Mentor and elevate other data scientists across the organization on relevance evaluation, experimentation best practices for ranking systems, causal reasoning, and statistical rigor
  • Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader relevance, recommendation systems, and experimentation community

Required Qualifications

  • Ph.D. in Statistics, Computer Science, Information Retrieval, Economics, or a related quantitative field with a strong focus on recommendation systems, ranking, causal inference, or evaluation methodology; or M.S. with equivalent depth of expertise
  • For M.S. holders: 12+ years of industry experience in applied science, data science, or relevance/ranking-focused roles
  • For Ph.D. holders: 8+ years of industry experience in applied science, data science, or relevance/ranking-focused roles
  • Deep expertise in metrics design and evaluation for ranking and recommendation systems, including offline metrics and counterfactual evaluation
  • Strong understanding of causal inference and experimentation methodology, including practical experience with challenges relevant to ranking systems such as novelty effects, position bias, long-run effect estimation, and ecosystem-level impacts
  • Experience defining and validating quality metrics for content ranking, search, or recommendations at scale
  • Strong theoretical grounding in experimental design, including power analysis, variance reduction techniques, and sequential testing as applied to relevance experiments
  • Expert knowledge of SQL and proficiency in R and/or Python for statistical computing
  • Demonstrated ability to influence product and organizational strategy through data-driven insights about content quality and user experience
  • Excellent communication skills with the ability to explain nuanced statistical and ML concepts and tradeoffs to both technical and non-technical senior stakeholders
  • Experience mentoring data scientists and building organizational capability in relevance evaluation and experimentation
  • Comfortable in innovative and fast-paced environments with a bias toward action

Preferred Qualifications

  • Published research or industry contributions in areas recommendation systems or causal inference for ranking
  • Experience with social network or user-generated content platforms where community-level dynamics create non-trivial relevance and experimentation challenges

Benefits:

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k with Employer Match
  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave

#LI-REMOTE

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$232,500—$325,500 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

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Data Analytics Senior Staff Data Scientist - Consumer Experimentation at Reddit, Inc.

Senior technical leader who designs and analyzes complex experiments across Reddit's consumer products, setting experimentation standards and ensuring causal inference rigor in a networked platform.

Lead Posted 4 days ago RemoteFirstJobs Product
What this role involves

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet.

Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes.

Reddit’s experimentation landscape presents uniquely challenging problems. Our platform is a deeply interconnected network of communities, contributors, and consumers – meaning that standard A/B testing assumptions often break down. We need a senior technical leader who thrives on these hard problems and can raise the bar for causal inference and experimentation rigor across the entire Consumer organization.

As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on experimentation methodology, owning the most complex and high-stakes experimentation challenges across Consumer. You will shape how Reddit learns from its experiments, ensure we draw valid causal conclusions in the presence of network effects and interference, and influence product strategy through rigorous experimental design and analysis.

Responsibilities:

  • Serve as the technical authority on experimentation methodology across Consumer, setting standards for design, analysis, and interpretation of experiments in a complex, networked environment
  • Tackle the hardest experimentation problems at Reddit, including spillover and network effects, interference between treatment and control, two-sided experimentation, and long-run effect estimation
  • Develop and advance methods for causal inference in settings where standard randomization assumptions are violated, such as cluster-randomized designs, switchback experiments, and synthetic control approaches
  • Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects, ensuring product teams can measure true causal impact rather than biased local estimates
  • Identify opportunities where improved experimentation methodology can unlock product insights that were previously unmeasurable or ambiguous
  • Build and scale self-serve experimentation tools, platforms, and best-practice documentation that increase experimentation velocity and literacy across product, engineering, and design teams
  • Influence the long-term product strategy by driving learning through well-designed experiments and translating experimental results into clear, actionable recommendations for senior leadership
  • Mentor and elevate other data scientists across the organization on experimentation best practices, causal reasoning, and statistical rigor
  • Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader experimentation and causal inference community

Required Qualifications:

  • Ph.D. in Statistics, Econometrics, Economics, Computer Science, or a related quantitative field with a strong focus on causal inference or experimentation methodology; or M.S. with equivalent depth of expertise
  • For M.S. holders: 12+ years of industry experience in applied science, data science, or experimentation-focused roles
  • For Ph.D. holders: 8+ years of industry experience in applied science, data science, or experimentation-focused roles
  • Deep expertise in causal inference, including practical experience with challenges such as network interference / spillovers, two-sided experimentation, switchback designs, cluster randomization, and/or synthetic control methods
  • Strong theoretical grounding in experimental design, including power analysis, variance reduction techniques, sequential testing, and multiple comparison corrections
  • Experience with experimentation platforms at scale (e.g., building or significantly extending an internal experimentation platform)
  • Expert knowledge of SQL and proficiency in R and/or Python for statistical computing
  • Track record of designing and analyzing experiments at scale in complex or networked environments
  • Demonstrated ability to influence product and organizational strategy through experimentation insights
  • Demonstrated ability to take ambiguous, technically complex problems and solve them in a structured, hypothesis-driven way
  • Excellent communication skills with the ability to explain nuanced statistical concepts and tradeoffs to both technical and non-technical senior stakeholders
  • Experience mentoring data scientists and building organizational capability in experimentation and causal reasoning
  • Comfortable in innovative and fast-paced environments with a bias toward action

Preferred Qualifications:

  • Published research or industry contributions in areas such as interference in experiments, network experimentation, or marketplace causal inference
  • Familiarity with Bayesian experimental methods, bandit algorithms, or adaptive experimental designs
  • Experience with social network or user-generated content platforms where community-level dynamics create non-trivial experimentation challenges

Benefits:

  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Comprehensive Medical Benefits & Health Care Spending Account
  • Registered Retirement Savings Plan with matching contributions
  • Income Replacement Programs
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave

#LI-REMOTE

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Read the full description
Data Analytics Senior Staff Data Scientist - Consumer Experimentation at Reddit, Inc.

Senior technical leader who sets experimentation methodology standards and solves complex causal inference challenges to inform Reddit's product strategy.

Lead Posted 4 days ago RemoteFirstJobs Product
What this role involves

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet.

Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes.

Reddit’s experimentation landscape presents uniquely challenging problems. Our platform is a deeply interconnected network of communities, contributors, and consumers – meaning that standard A/B testing assumptions often break down. We need a senior technical leader who thrives on these hard problems and can raise the bar for causal inference and experimentation rigor across the entire Consumer organization.

As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on experimentation methodology, owning the most complex and high-stakes experimentation challenges across Consumer. You will shape how Reddit learns from its experiments, ensure we draw valid causal conclusions in the presence of network effects and interference, and influence product strategy through rigorous experimental design and analysis.

Responsibilities:

  • Serve as the technical authority on experimentation methodology across Consumer, setting standards for design, analysis, and interpretation of experiments in a complex, networked environment
  • Tackle the hardest experimentation problems at Reddit, including spillover and network effects, interference between treatment and control, two-sided experimentation, and long-run effect estimation
  • Develop and advance methods for causal inference in settings where standard randomization assumptions are violated, such as cluster-randomized designs, switchback experiments, and synthetic control approaches
  • Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects, ensuring product teams can measure true causal impact rather than biased local estimates
  • Identify opportunities where improved experimentation methodology can unlock product insights that were previously unmeasurable or ambiguous
  • Build and scale self-serve experimentation tools, platforms, and best-practice documentation that increase experimentation velocity and literacy across product, engineering, and design teams
  • Influence the long-term product strategy by driving learning through well-designed experiments and translating experimental results into clear, actionable recommendations for senior leadership
  • Mentor and elevate other data scientists across the organization on experimentation best practices, causal reasoning, and statistical rigor
  • Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader experimentation and causal inference community

Required Qualifications:

  • Ph.D. in Statistics, Econometrics, Economics, Computer Science, or a related quantitative field with a strong focus on causal inference or experimentation methodology; or M.S. with equivalent depth of expertise
  • For M.S. holders: 12+ years of industry experience in applied science, data science, or experimentation-focused roles
  • For Ph.D. holders: 8+ years of industry experience in applied science, data science, or experimentation-focused roles
  • Deep expertise in causal inference, including practical experience with challenges such as network interference / spillovers, two-sided experimentation, switchback designs, cluster randomization, and/or synthetic control methods
  • Strong theoretical grounding in experimental design, including power analysis, variance reduction techniques, sequential testing, and multiple comparison corrections
  • Experience with experimentation platforms at scale (e.g., building or significantly extending an internal experimentation platform)
  • Expert knowledge of SQL and proficiency in R and/or Python for statistical computing
  • Track record of designing and analyzing experiments at scale in complex or networked environments
  • Demonstrated ability to influence product and organizational strategy through experimentation insights
  • Demonstrated ability to take ambiguous, technically complex problems and solve them in a structured, hypothesis-driven way
  • Excellent communication skills with the ability to explain nuanced statistical concepts and tradeoffs to both technical and non-technical senior stakeholders
  • Experience mentoring data scientists and building organizational capability in experimentation and causal reasoning
  • Comfortable in innovative and fast-paced environments with a bias toward action

Preferred Qualifications:

  • Published research or industry contributions in areas such as interference in experiments, network experimentation, or marketplace causal inference
  • Familiarity with Bayesian experimental methods, bandit algorithms, or adaptive experimental designs
  • Experience with social network or user-generated content platforms where community-level dynamics create non-trivial experimentation challenges

Benefits:

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k with Employer Match
  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave

#LI-REMOTE

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$232,500—$325,500 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Read the full description
Data Analytics Data Platform Architect at TailorCare

Lead the design and strategy of a healthcare data platform that ingests clinical and claims data, performs real-time patient scoring and decisioning, and ensures HIPAA compliance and AI governance.

Lead Hybrid Posted 4 days ago RemoteFirstJobs Product
What this role involves

About the Role

TailorCare is a value-based musculoskeletal (MSK) care platform combining clinical expertise, digital tools, and a yield-based operating model. We are now operationalizing Operating Model 3.0, a shift from uniform delivery to yield-based alignment, in which every patient receives investment proportional to a real-time Yield Score (Probability × Value × Addressability), and an ROI Gate continuously calibrates Wallet (financial investment) and Muscle (operational intensity).

This requires a data and AI platform that ingests, resolves, scores, decides, and acts in minutes, with the explainability and governance healthcare demands. You will lead that build: set the strategy, design the data platform, drive vendor decisions, and partner with engineering, product, clinical, and operations leadership to deliver it. This is a hybrid strategy-and-architecture role; you will move comfortably from a CTO whiteboard conversation to an EDI 837 parser to a model-evaluation review without losing the thread.

Primary Responsibilities

  • Set strategy. Own the multi-year data strategy supporting Operating Model optimization and TailorCare’s extension beyond MSK; frame tradeoffs for the executive team; protect strategic data moats (canonical patient and provider graphs, proprietary outcome labels, and contribute to yield-calibrated decisioning IP)
  • Architect the platform end-to-end. Ingestion, event bus, identity resolution, lakehouse, feature store, ROI Gate decisioning, action orchestration, observability. Define the event taxonomy, schema registry, and data contracts that govern how every source flows in
  • Lead vendor strategy. Evaluate and select across clearinghouses, clinical networks, claims systems, provider intelligence, conversational AI, CDPs, and more, negotiating export rights, schema stability, and contribute to defining BAA scope. Build payer-neutral patterns from day one
  • Set the bar for HIPAA, PHI, and AI governance. Classification at ingestion, field-level access controls, infrastructure-level scrubbing, vendor data governance, training-data lineage, and consent chains.
  • Partner across functions. Translate architecture into staffed delivery with each engineering team; collaborate with clinical leadership on Patient Reported Outcome, extraction accuracy, and outcome labels; work with operations to make the intake and data aggregation meaningful.
  • Other duties as assigned

Qualifications

  • 10+ years working with healthcare data, including 4+ years in architecture or strategy leadership
  • Deep hands-on knowledge of healthcare data: X12 EDI (270/271/276/277/278/834/835/837), FHIR R4, HL7 v2 (especially ADT), CCD/C-CDA, NCPDP, and the realities of integrating with payers, EHRs, clearinghouses, and HIEs
  • Experience working with AI team developing predictive models and ability to act as the liaison between AI modeling and data platform.
  • Proven track record designing production data platforms at scale, streaming and batch, with managed Kafka or equivalent, lakehouse architectures (Snowflake / Databricks / BigQuery), dbt-style orchestration, modern observability
  • Solid grounding in ML/AI systems: feature stores, point-in-time correctness, model lifecycle, NLP for clinical text. You evaluate model proposals on their merits
  • Direct experience with patient identity resolution (deterministic + probabilistic) and tokenization (Datavant or equivalent)
  • Working knowledge of value-based care economics: MLR, attribution, episode costing, risk adjustment, and how reimbursement models shape data requirements
  • Demonstrated executive presence: framing tradeoffs, defending recommendations, adjusting when wrong, staying technically credible
  • HIPAA-fluent. You engineer PHI minimization, BAA structures, and audit requirements as first-class concerns
  • Ability and willingness to travel up to 10% as needed for onsite meetings, team collaboration, and company events.

Preferred Qualifications

  • Hands-on experience with at least one major longitudinal claims dataset (Komodo, Truveta, HealthVerity, Optum, IQVIA) and integration
  • Highly collaborative and experienced with a broad range of business holders
  • Experience integrating clinical data networks
  • Experience with conversational AI in a contact-center context (Cresta, Observe.AI, or built in-house)
  • Multi-payer scale experience
  • Early-stage / scaling startup background, comfort with ambiguity and the ability to make calls without perfect information

What you will deliver in year one

  • Be a key leader in driving build vs. buy data acquisition decisions
  • Canonical patient master service in production; ≥95% deterministic match rate, documented probabilistic strategy
  • Real-time event bus with ≥10 production event types, SLO dashboards, and downstream consumers live
  • Real-time ADT, eligibility (270⁄271) and prior-auth (278) integrations live with sub-second response
  • Salesforce (TailorCare-captured) clinical operational data fully instrumented
  • Clinical data network integration (Health Gorilla or Particle) with NLP extraction on radiology and specialist notes
  • ROI Gate v1 deployed, routing ≥80% of newly-identified patients; closed-loop attribution from marketing to outcome operational

What’s In It For You

  • Meaningful Work: We are dedicated to our mission and deeply value our patients and each other. Each day offers the opportunity to make a positive impact.
  • Work Environment: We operate as a remote-first company with options for a hybrid work model in Nashville.
  • Time Off: Our generous paid time off (PTO) and holiday plans ensure you have ample time to rest and recharge.
  • Family First: We offer paid parental leave and support a healthy work-life balance, encouraging flexibility and autonomy. We love talking about our family and pets!
  • Comprehensive Benefits: From Day 1, employees enjoy medical, dental, vision, life, and disability insurance, wellness resources and an employer HSA contribution.
  • Fair Compensation: We are committed to equitable pay for all team members and support your future goals with a 401k plan that includes employer matching.
  • Community: We foster an inclusive environment where you can rely on your teammates, share honest feedback, and feel comfortable being your authentic self at work each day.

TailorCare seeks to recruit and retain staff from diverse backgrounds and encourages qualified candidates to apply. TailorCare is an equal opportunity employer and does not discriminate on the basis of age, sex, gender identity/expression, sexual orientation, color, race, creed, national origin, ancestry, religion, marital status, political belief, physical or mental disability, pregnancy, military, or veteran status.

Read the full description
Data Analytics Senior Staff Data Scientist at Reddit, Inc.

Senior Staff Data Scientist leading relevance measurement and evaluation strategy, defining metrics and analytical frameworks to improve content ranking and recommendations across Reddit's consumer platform.

Lead Posted 4 days ago RemoteFirstJobs Product
What this role involves

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet.

Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes.

Reddit’s relevance challenges are uniquely complex. Our platform is a deeply interconnected network of communities, contributors, and consumers - where the notion of “relevance” spans personalized content ranking, community discovery, and search across an enormous corpus of authentic, user-generated content. We need a senior technical leader who thrives on these hard problems and can raise the bar for how we measure, evaluate, and improve the quality of recommendations and search results across the entire Consumer organization.

As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on relevance measurement and evaluation, partnering closely with Feeds and Search ML teams to tackle the most complex ranking, recommendation, and retrieval challenges across Consumer. You will shape how Reddit understands content quality, define the metrics and analytical frameworks that guide relevance improvements, and influence product strategy through rigorous analysis and experimentation.

Responsibilities

  • Serve as the technical authority on relevance metrics and evaluation methodology across Consumer, setting standards for how we measure the quality of feeds, search results, and recommendations in a complex, community-driven environment
  • Develop metrics frameworks and offline evaluation approaches for ranking and recommendation systems, including proxy metrics that reliably predict long-term outcomes like retention, community health, and user satisfaction
  • Design and analyze experiments for relevance features, accounting for challenges unique to networked platforms such as spillover effects between communities, interference between contributors and consumers, and long-run impacts of ranking changes on content supply
  • Identify opportunities where improved measurement and analysis can unlock product insights that were previously unmeasurable or ambiguous, particularly around content quality, search intent understanding, and personalization effectiveness
  • Partner deeply with ML engineers and product teams to translate model performance metrics into user-facing impact
  • Influence the long-term product strategy for Feeds and Search by synthesizing insights from experimentation, observational analysis, and metric deep-dives into clear, actionable recommendations for senior leadership
  • Mentor and elevate other data scientists across the organization on relevance evaluation, experimentation best practices for ranking systems, causal reasoning, and statistical rigor
  • Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader relevance, recommendation systems, and experimentation community

Required Qualifications

  • Ph.D. in Statistics, Computer Science, Information Retrieval, Economics, or a related quantitative field with a strong focus on recommendation systems, ranking, causal inference, or evaluation methodology; or M.S. with equivalent depth of expertise
  • For M.S. holders: 12+ years of industry experience in applied science, data science, or relevance/ranking-focused roles
  • For Ph.D. holders: 8+ years of industry experience in applied science, data science, or relevance/ranking-focused roles
  • Deep expertise in metrics design and evaluation for ranking and recommendation systems, including offline metrics and counterfactual evaluation
  • Strong understanding of causal inference and experimentation methodology, including practical experience with challenges relevant to ranking systems such as novelty effects, position bias, long-run effect estimation, and ecosystem-level impacts
  • Experience defining and validating quality metrics for content ranking, search, or recommendations at scale
  • Strong theoretical grounding in experimental design, including power analysis, variance reduction techniques, and sequential testing as applied to relevance experiments
  • Expert knowledge of SQL and proficiency in R and/or Python for statistical computing
  • Demonstrated ability to influence product and organizational strategy through data-driven insights about content quality and user experience
  • Excellent communication skills with the ability to explain nuanced statistical and ML concepts and tradeoffs to both technical and non-technical senior stakeholders
  • Experience mentoring data scientists and building organizational capability in relevance evaluation and experimentation
  • Comfortable in innovative and fast-paced environments with a bias toward action

Preferred Qualifications

  • Published research or industry contributions in areas recommendation systems or causal inference for ranking
  • Experience with social network or user-generated content platforms where community-level dynamics create non-trivial relevance and experimentation challenges

Benefits:

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k with Employer Match
  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave

#LI-REMOTE

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$232,500—$325,500 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Read the full description
Data Analytics Senior Staff Data Scientist - Consumer Experimentation at Reddit, Inc.

Senior technical leader designing and analyzing complex experiments to understand user behavior and inform product strategy across Reddit's consumer platform.

Lead Posted 4 days ago RemoteFirstJobs Product
What this role involves

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet.

Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes.

Reddit’s experimentation landscape presents uniquely challenging problems. Our platform is a deeply interconnected network of communities, contributors, and consumers – meaning that standard A/B testing assumptions often break down. We need a senior technical leader who thrives on these hard problems and can raise the bar for causal inference and experimentation rigor across the entire Consumer organization.

As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on experimentation methodology, owning the most complex and high-stakes experimentation challenges across Consumer. You will shape how Reddit learns from its experiments, ensure we draw valid causal conclusions in the presence of network effects and interference, and influence product strategy through rigorous experimental design and analysis.

Responsibilities:

  • Serve as the technical authority on experimentation methodology across Consumer, setting standards for design, analysis, and interpretation of experiments in a complex, networked environment
  • Tackle the hardest experimentation problems at Reddit, including spillover and network effects, interference between treatment and control, two-sided experimentation, and long-run effect estimation
  • Develop and advance methods for causal inference in settings where standard randomization assumptions are violated, such as cluster-randomized designs, switchback experiments, and synthetic control approaches
  • Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects, ensuring product teams can measure true causal impact rather than biased local estimates
  • Identify opportunities where improved experimentation methodology can unlock product insights that were previously unmeasurable or ambiguous
  • Build and scale self-serve experimentation tools, platforms, and best-practice documentation that increase experimentation velocity and literacy across product, engineering, and design teams
  • Influence the long-term product strategy by driving learning through well-designed experiments and translating experimental results into clear, actionable recommendations for senior leadership
  • Mentor and elevate other data scientists across the organization on experimentation best practices, causal reasoning, and statistical rigor
  • Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader experimentation and causal inference community

Required Qualifications:

  • Ph.D. in Statistics, Econometrics, Economics, Computer Science, or a related quantitative field with a strong focus on causal inference or experimentation methodology; or M.S. with equivalent depth of expertise
  • For M.S. holders: 12+ years of industry experience in applied science, data science, or experimentation-focused roles
  • For Ph.D. holders: 8+ years of industry experience in applied science, data science, or experimentation-focused roles
  • Deep expertise in causal inference, including practical experience with challenges such as network interference / spillovers, two-sided experimentation, switchback designs, cluster randomization, and/or synthetic control methods
  • Strong theoretical grounding in experimental design, including power analysis, variance reduction techniques, sequential testing, and multiple comparison corrections
  • Experience with experimentation platforms at scale (e.g., building or significantly extending an internal experimentation platform)
  • Expert knowledge of SQL and proficiency in R and/or Python for statistical computing
  • Track record of designing and analyzing experiments at scale in complex or networked environments
  • Demonstrated ability to influence product and organizational strategy through experimentation insights
  • Demonstrated ability to take ambiguous, technically complex problems and solve them in a structured, hypothesis-driven way
  • Excellent communication skills with the ability to explain nuanced statistical concepts and tradeoffs to both technical and non-technical senior stakeholders
  • Experience mentoring data scientists and building organizational capability in experimentation and causal reasoning
  • Comfortable in innovative and fast-paced environments with a bias toward action

Preferred Qualifications:

  • Published research or industry contributions in areas such as interference in experiments, network experimentation, or marketplace causal inference
  • Familiarity with Bayesian experimental methods, bandit algorithms, or adaptive experimental designs
  • Experience with social network or user-generated content platforms where community-level dynamics create non-trivial experimentation challenges

Benefits:

  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Comprehensive Medical Benefits & Health Care Spending Account
  • Registered Retirement Savings Plan with matching contributions
  • Income Replacement Programs
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave

#LI-REMOTE

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Read the full description
Data Analytics Senior Staff Data Scientist - Consumer Experimentation at Reddit, Inc.

Senior technical leader who designs and analyzes complex experiments to measure causal impact of product changes on Reddit's consumer experience.

Lead Posted 4 days ago RemoteFirstJobs Product
What this role involves

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet.

Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes.

Reddit’s experimentation landscape presents uniquely challenging problems. Our platform is a deeply interconnected network of communities, contributors, and consumers – meaning that standard A/B testing assumptions often break down. We need a senior technical leader who thrives on these hard problems and can raise the bar for causal inference and experimentation rigor across the entire Consumer organization.

As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on experimentation methodology, owning the most complex and high-stakes experimentation challenges across Consumer. You will shape how Reddit learns from its experiments, ensure we draw valid causal conclusions in the presence of network effects and interference, and influence product strategy through rigorous experimental design and analysis.

Responsibilities:

  • Serve as the technical authority on experimentation methodology across Consumer, setting standards for design, analysis, and interpretation of experiments in a complex, networked environment
  • Tackle the hardest experimentation problems at Reddit, including spillover and network effects, interference between treatment and control, two-sided experimentation, and long-run effect estimation
  • Develop and advance methods for causal inference in settings where standard randomization assumptions are violated, such as cluster-randomized designs, switchback experiments, and synthetic control approaches
  • Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects, ensuring product teams can measure true causal impact rather than biased local estimates
  • Identify opportunities where improved experimentation methodology can unlock product insights that were previously unmeasurable or ambiguous
  • Build and scale self-serve experimentation tools, platforms, and best-practice documentation that increase experimentation velocity and literacy across product, engineering, and design teams
  • Influence the long-term product strategy by driving learning through well-designed experiments and translating experimental results into clear, actionable recommendations for senior leadership
  • Mentor and elevate other data scientists across the organization on experimentation best practices, causal reasoning, and statistical rigor
  • Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader experimentation and causal inference community

Required Qualifications:

  • Ph.D. in Statistics, Econometrics, Economics, Computer Science, or a related quantitative field with a strong focus on causal inference or experimentation methodology; or M.S. with equivalent depth of expertise
  • For M.S. holders: 12+ years of industry experience in applied science, data science, or experimentation-focused roles
  • For Ph.D. holders: 8+ years of industry experience in applied science, data science, or experimentation-focused roles
  • Deep expertise in causal inference, including practical experience with challenges such as network interference / spillovers, two-sided experimentation, switchback designs, cluster randomization, and/or synthetic control methods
  • Strong theoretical grounding in experimental design, including power analysis, variance reduction techniques, sequential testing, and multiple comparison corrections
  • Experience with experimentation platforms at scale (e.g., building or significantly extending an internal experimentation platform)
  • Expert knowledge of SQL and proficiency in R and/or Python for statistical computing
  • Track record of designing and analyzing experiments at scale in complex or networked environments
  • Demonstrated ability to influence product and organizational strategy through experimentation insights
  • Demonstrated ability to take ambiguous, technically complex problems and solve them in a structured, hypothesis-driven way
  • Excellent communication skills with the ability to explain nuanced statistical concepts and tradeoffs to both technical and non-technical senior stakeholders
  • Experience mentoring data scientists and building organizational capability in experimentation and causal reasoning
  • Comfortable in innovative and fast-paced environments with a bias toward action

Preferred Qualifications:

  • Published research or industry contributions in areas such as interference in experiments, network experimentation, or marketplace causal inference
  • Familiarity with Bayesian experimental methods, bandit algorithms, or adaptive experimental designs
  • Experience with social network or user-generated content platforms where community-level dynamics create non-trivial experimentation challenges

Benefits:

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k with Employer Match
  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave

#LI-REMOTE

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$232,500—$325,500 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

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Data Analytics Lead Business Analyst (Enterprise Modernisation, Platform and Cloud)

Leads business analysis for enterprise modernization and cloud platform initiatives, bridging client needs with technical solutions.

Lead Posted 5 days ago Jobicy AI
What this role involves
What happens when you have fascinating clients with challenging problems on the one hand and passionate software developers looking to build future-focused solutions on the other? This in-between is where...
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Data Analytics Lead Business Analyst (Enterprise Modernisation, Platform and Cloud)

Analyzes business requirements and data for enterprise modernization projects, bridging client needs with software development solutions.

Lead Posted 5 days ago Jobicy AI
What this role involves
What happens when you have fascinating clients with challenging problems on the one hand and passionate software developers looking to build future-focused solutions on the other? This in-between is where...
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Data Analytics Lead Data Scientist at AppOmni

Lead Data Scientist designs and implements scalable data pipelines, statistical models, and ML systems to transform complex datasets into actionable product insights and customer-facing analytics capabilities.

Lead Posted 6 days ago RemoteFirstJobs Product
What this role involves

About AppOmni

AppOmni prevents SaaS data breaches by delivering end-to-end SaaS security. Our platform gives security teams clear visibility into posture, access, third-party connections, AI-related activity, and with built-in discovery to identify unsanctioned SaaS and Shadow AI tools. Backed by continuous monitoring and real-time threat detection, AppOmni helps enterprises identify and resolve risks early, keeping their SaaS applications secure.

Recognized as a Frost Radar™ 2025 Leader and Great Place To Work ®, AppOmni continues to set the standard for innovation and customer value in SaaS security. The largest and fastest-growing global enterprises across industries trust AppOmni to secure their SaaS applications.

About the Role

AppOmni is looking for a Lead Data Scientist to help define and build scalable, production-grade data pipelines and intelligent analytics capabilities within our SaaS platform.

In this role, you will apply data science, statistical modeling, batch and real-time analytics, and large-scale data engineering to transform complex datasets into actionable product insights and customer-facing capabilities. You will work across a broad range of technical domains on pipelines, including ETL, statistical modeling, machine learning (supervised and unsupervised) and LLM as well as monitoring, governance, visualization, and production modeling systems.

We are looking for a highly versatile engineer-scientist — someone who has worked across different layers of the modern data stack and enjoys continuing to solve a wide variety of technical problems. This role is ideal for someone whose background spans data engineering, infrastructure, analytics applications, statistical modeling, and operational production systems.

You will be responsible for end-to-end data workflows, from ingestion and transformation through analytics implementation, orchestration, monitoring, governance, and production operations. This is a hands-on individual contributor role with technical leadership responsibilities, partnering closely with Product and Engineering to build reliable, scalable, and intelligent data-driven systems

What You’ll Do

  • Design and implement scalable batch and real-time data processing systems across large and complex datasets.
  • Build and optimize ETL and streaming data pipelines using modern GCP big data technologies.
  • Lead development decisions around model choices, data architecture, data modeling, pipeline orchestration, analytics infrastructure, and production systems.
  • Develop statistical models and analytics capabilities that support product intelligence and operational insights.
  • Design and maintain production-grade data workflows using technologies such as Airflow, Dataflow, PubSub, and PySpark.
  • Contribute across multiple areas of the data ecosystem, including data engineering, monitoring and governance, visualization, and analytics tooling.
  • Establish monitoring, observability, and governance practices for data quality, pipeline reliability, and production health.
  • Partner closely with Engineering to operationalize scalable data infrastructure and analytics systems.
  • Collaborate with Product to shape intelligent, data-driven product capabilities and user experiences.
  • Act as a technical leader and thought partner across data engineering, analytics, infrastructure, and applied modeling initiatives.
  • Help evolve internal tooling and frameworks that improve scalability, reliability, and operational efficiency across the platform.

What We’re Looking For

  • 7–10+ years of experience as a Data Scientist, Applied Scientist, Data Engineer, or Machine Learning Engineer, with ownership of production systems.
  • Strong experience building and operating large-scale data pipelines and distributed data processing systems.
  • Hands-on experience within the GCP ecosystem, particularly big data services such as Dataproc, Dataflow, PubSub, and related storage and data lake technologies.
  • Strong proficiency in Python, PySpark, and modern data processing frameworks.
  • Experience working across multiple disciplines of the data stack, including data engineering, analytics, infrastructure, monitoring/governance, APIs, and visualization.
  • Experience with real-time or streaming systems and orchestration frameworks such as Airflow and Apache Beam/Dataflow.
  • Strong foundation in statistical modeling, analytics, and applied data science techniques.
  • Experience designing and maintaining scalable ETL workflows and production data infrastructure.
  • Familiarity with monitoring, observability, governance, and reliability practices for production data systems.
  • Ability to thrive in highly cross-functional environments and contribute across a wide range of technical challenges.
  • Demonstrated versatility — a background that spans multiple types of data applications, infrastructure, and analytics work is highly valued.
  • Experience partnering closely with Product and Engineering to deliver customer-facing capabilities.
  • Strong written and verbal communication skills.

Culture

Our talented team is collaborative and supportive as we move quickly to research and develop new ideas, deliver new features to our customers, and iterate on ideas and innovations. We accomplish this by focusing on our five core values: Trust, Transparency, Quality, Customer Focus, and Delivery. Our team is determined to make a difference to positively impact our way of life by securing the technology that is changing the world.

AppOmni is proud to be Certified by Great Place to WorkⓇ, as we seek to build a culture where all employees feel appreciated and supported, especially with clear and honest leadership, employee recognition, and an environment that fosters innovation and collaboration.

We believe diversity fuels innovation and drives growth by bringing a wealth of different perspectives and skills. We’re committed to fostering an inclusive environment where every employee feels valued, heard, and empowered to reach their full potential. Join us in building a workplace where we can all thrive.

Compensation & Benefits

AppOmni is committed to supporting our employees’ financial, professional, and personal well-being. To do this, we take a holistic view of compensation, one that values not just the immediate financial package but also the long-term growth of both our employees and our company. We’re committed to pay equity and transparency and encourage all candidates to discuss their salary expectations with us early in the application process.

Our total rewards package includes the following:

  • Base Salary: The annual base salary compensation range in the U.S. for this role is: $210,000 - $240,000 USD. Higher compensation may be available for candidates in higher cost of living markets.  Final offer amounts are determined by factors such as the final candidate’s skills, qualifications, and experience, as well as business considerations and peer compensation.
  • Stock Options: Our vision is to not just grow as a company but to grow together. By offering stock options, we are inviting you to be an integral part of our journey forward.
  • Benefits: Generous paid time off, paid company holidays, paid floating holidays, paid parental leave, paid sick time and paid family leave for applicable states, health insurance - medical, dental, and vision with HSA option, LifeWorks Employee Assistance Program, company-provided life insurance, AD&D, STD/LTD and additional supplemental life insurance options, 401(k) and Roth retirement saving accounts, and a monthly wellness benefit reimbursement. All benefits are subject to eligibility requirements and plan details.

AppOmni is an equal-opportunity employer. Applicants will not be discriminated against because of race, color, creed, national origin, ancestry, citizenship status, sex, sexual orientation, gender identity or expression, age, religion, disability, pregnancy, marital status, veteran status, medical condition, genetic information, or any other characteristic protected by law. AppOmni is also committed to providing reasonable accommodations to qualified individuals with disabilities and disabled veterans in our job application procedures.

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Data Analytics Airalo: Staff Data Analyst, Product

Staff Data Analyst owns product analytics, partnering with product teams and leadership to drive data-backed decisions on user activation, engagement, retention, and revenue.

Lead Remote Posted 8 days ago We Work Remotely — Programming
What this role involves

Headquarters: Spain / United Kingdom

About AiraloAlo! Airalo is the world’s first eSIM store that helps people connect in over 200+ countries and regions across the globe. We are building the next digital service that revolutionizes the telecom industry. We are a travel-tech company and an equal-opportunity environment that values and executes diversity, inclusion, and equity. Our team is spread across 50+ countries and six continents. What glues us together is our commitment to changing the way you connect. Check out more information about Airalo in our Public Handbook: https://airalo-public.notion.site/airalo-public-handbook
About youWe hope that you care deeply about the quality of your work, the intrinsic worth of tasks, and the success of your team. You are self-disciplined and do not require micromanagement in terms of your skillset and work ethic. You do your best to flourish as an individual every day while working hard to foster a collaborative team environment. You believe in the importance of being — and staying — authentic, honest, positive, and kind. You are a good interlocutor with clear and concise communication. You are able to manage multiple projects, have an analytical mind, pay keen attention to detail, and love to get your hands dirty. You are cognizant, tolerant, and welcoming of vulnerabilities and cultural differences.
About the RolePosition: Full-time / EmployeeLocation: Remote-first Benefits: Health Insurance, work-from-anywhere stipend, annual wellness & learning credits, annual all-expenses-paid company retreat in a gorgeous destination & other benefits
We're looking for a Staff Data Analyst, Product to own product analytics at Airalo. You'll be the go-to person for understanding how our 20M+ users across 190+ countries interact with our product-what drives activation, engagement, retention, and ultimately revenue. This is a high-impact IC role with significant scope: you'll partner directly with product teams and leadership  to shape product strategy through data.
You'll report to the Director of Data and partner closely with analytics engineering, product managers, and cross-functional stakeholders. Success looks like product decisions backed by rigorous analysis, experimentation that compounds learning, and metrics the business trusts and uses. Beyond delivering insights that influence the roadmap, you'll help shape how product analytics operates at Airalo-our model is evolving, and you'll have real input into how we scale coverage and structure the team.

What you’ll do:

    • Partner with Product teams to define success metrics, design experiments, and evaluate feature impact
    • Partner with fractional squad analysts where they exist; serve as the primary analytics partner for squads without dedicated coverage and help evolve our organisational model for product analytics
    • Be hands-on with analysis, dashboards, and metric development while building the foundations for a scalable product analytics practice
    • Define, own, and govern product metrics and KPIs in alignment with our company-wide unified KPI framework-ensuring consistency, clarity, and trust in how we measure product performance in alignment with business goals
    • Build and maintain core product health dashboards in partnership with analytics engineering as we’re transitioning to self-service via Lightdash and maturing our analytics platform
    • Conduct deep-dive analyses on user behavior, funnel performance, and cohort trends to surface opportunities and diagnose issues
    • Design and analyze A/B tests and experiments, establishing best practices for experimentation rigor
    • Translate complex analytical findings into clear recommendations for technical and non-technical stakeholders, including executive leadership
    • Partner with data and product teams, to define data requirements and ensure product event tracking meets analytical needs

Must-haves:

    • 7+ years in product analytics, data science, or quantitative analytics roles, with demonstrated impact at staff/principal level
    • Deep experience with product analytics in a B2C or marketplace environment-you understand funnels, retention curves, and user lifecycle intimately
    • Track record of defining and owning metrics frameworks-you've established KPIs, driven cross-functional alignment, and maintained metric integrity as products and teams scaled
    • Strong SQL skills and proficiency in Python or R for statistical analysis and modeling
    • Proven track record designing and analyzing experiments, with solid understanding of statistical methods and common pitfalls
    • Experience with product analytics tools (Amplitude, Mixpanel, or similar) and modern BI platforms
    • Ability to translate ambiguous business questions into structured analytical approaches
    • Excellent communication skills-you can tell a compelling story with data and influence product decisions at the leadership level
    • Strong business intuition and user empathy; you think beyond the data to understand the "why"
    • Comfortable operating with autonomy in a fast-moving environment where not everything is well-defined-you bring structure without waiting for permission
    • You've been the person who brought rigor to a team that didn't have it-introduced frameworks, challenged assumptions, and shifted how product teams think about data

Good to Have:

    • Experience in marketplace, telecom, travel or subscription/usage-based businesses
    • Experience building experimentation programs or platforms from scratch-culture, tooling, and processes
    • Previous work at a scale-up during hypergrowth, where you've seen what breaks and what scales
    • You've been the person who brought rigor to a team that didn't have it-introduced frameworks, challenged assumptions, and shifted how product teams think about data
By applying, you acknowledge and agree that, in case of successful application, Airalo may request to run background checks as a condition for entering into an agreement with you. Rest assured that these checks will only occur upon your prior consent and at the end of the selection process, and will be strictly limited to what is allowed under the laws that are applicable to you. All data that you share or that we collect in connection with such checks will be processed in accordance with our Privacy Policy, available here: https://www.airalo.com/more-info/privacy-policy?srsltid=AfmBOooBT0rXAj1FaNelZ3VfN0wvhwzvAoxdtHnOKSVETpiSjiXVuycy
We sincerely thank all applicants in advance for submitting their interest in this opportunity. Airalo is an equal-opportunity employer and values diversity, equity & inclusion. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to providing reasonable accommodations upon request for individuals with disabilities throughout our job interview process.We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

To apply: https://weworkremotely.com/remote-jobs/airalo-staff-data-analyst-product

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Data Analytics Lead Insurance Pricing Analyst

Analyzes insurance pricing data and models to support pricing strategy and financial decision-making.

Lead Posted 8 days ago Jobicy AI
What this role involves
🚀 We’re on a mission to make money work for everyone. We’re waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our...
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Data Analytics Data Science Lead at Prove

Data Science Lead designs scalable data architectures, leads R&D on novel data sources, and establishes analytical methodologies to support ML modeling and production analytics solutions.

Lead Remote Posted 8 days ago RemoteFirstJobs Product
What this role involves

About Prove

As the world moves to a mobile-first economy, businesses need to modernize how they acquire, engage with and enable consumers. Prove’s phone-centric identity tokenization and passive cryptographic authentication solutions reduce friction, enhance security and privacy across all digital channels, and accelerate revenues while reducing operating expenses and fraud losses. Over 1,000 enterprise customers use Prove’s platform to process 20 billion customer requests annually across industries, including banking, lending, healthcare, gaming, crypto, e-commerce, marketplaces, and payments. For the latest updates from Prove, follow us on LinkedIn.

Prove is driving the future of digital identity. We are looking for Provers who know how to make an impact. We’re talking self-starting professionals who thrive in a fast-paced environment, process information quickly, and make intelligent decisions. The work is challenging and requires not only smart but natural curiosity and tenacity. Teamwork is also important to us – we work together and play together.

Prove has big plans, and we’re excited about the future. If this sounds like the place for you – come join our team!

Title: Data Science Lead

Department: Business Operations

Reports To: Director, Data Science

FLSA Status: Exempt

Location: US Remote

This role is not eligible for work authorization sponsorship.

Summary:

The Data Science Lead will serve as the strategic architect and research pioneer for the organization’s data ecosystem. This role is responsible for designing robust data architectures, leading research and development (R&D) for novel data sources, establishing rigorous analytical methodologies, and ensuring the seamless, scalable ingestion of high-quality data into downstream production solutions.

Core Pillars of Responsibility

1. Data Architecture & Scalable Engineering

  • Blueprint Design: Design and oversee the evolution of scalable data architectures that support advanced analytics, machine learning (ML) modeling, and real-time processing.

2. R&D & Novel Data Source Evaluation

  • Exploratory Research: Scout, evaluate, and pressure-test new internal, external, and alternative data sources (e.g., synthetic data, IoT streams, third-party APIs) for predictive power and commercial viability. Lead the ideation and feature engineering for these data sources and document how it aligns to current and future data architecture designs.
  • Proof of Concepts (PoCs): Lead rapid prototyping and PoCs to validate new technologies, algorithms, and data structures before scaling them to production.
  • Vendor & Partner Assessment: Technical vetting of data vendors and partners to ensure data quality, density, and seamless integration capabilities.

3. Methodology & Analytical Rigor

  • Framework Standardization: Define and document the organization’s gold-standard methodologies for statistical analysis, experimental design (A/B testing), and ML modeling.
  • Evaluation Metrics: Establish rigorous validation protocols and evaluation metrics (e.g., precision/recall, drift detection, bias/fairness audits) to ensure model and data integrity.
  • Continuous Improvement: Keep the organization at the cutting edge of data science by translating academic research and emerging industry trends into practical business methodologies.

4. Ingestion & Solution Integration

  • Productionalization Bridge: Serve as the critical bridge between R&D and Production, ensuring that complex analytical models and data sources are seamlessly ingested into core business products and solutions.
  • API & Interface Design: Oversee data delivery contracts between the DS ecosystem and downstream software applications to ensure the creation of clean, well-documented APIs.

Key Deliverables (First 12 Months)

  • Data Source Playbook: A formalized framework for scoring, vetting, and onboarding new data assets.
  • Methodology Registry: A centralized repository of approved statistical models, evaluation metrics, and ingestion protocols to ensure team-wide consistency.
  • Feature Importance Registry & Feature Engineering Roadmap: a centralized repository connecting current data sources to their product value and impact of removal and/or possible substitutes to the roadmap of how Prove can leverage the signals in new and differentiated ways
  • Architectural Roadmap: A 12 month to 3-year vision aligning data science infrastructure with corporate scaling goals.

Profile & Qualifications

  • 6+ years in Data Science/Data Engineering, with at least 2 years in a technical leadership or architectural role.
  • Technical Stack
  • Python, R, SQL, Cloud Platforms (AWS/GCP/Azure), Big Data tech (Spark, Kafka), Orchestration (Airflow), and MLOps tools.
  • Expertise
  • Deep understanding of data modeling, schema design (SQL/NoSQL), statistical evaluation, and MLOps deployment patterns, especially in R&D functions that bridge research with production.
  • Soft Skills
  • Exceptional ability to translate complex technical architectures into strategic business value for non-technical stakeholders.

This position description should not be considered the final description of the position. The position description is not intended to be an all-inclusive list of duties and standards of the positions. It should be assumed that we would, to some extent, structure responsibilities in accordance with the successful candidate’s capabilities and changing business conditions. Incumbents will follow any other instructions, and perform any other related duties, as assigned by their supervisor.

The anticipated salary range for this role is $179,000 - 200,000 plus variable commission / company bonus. Offered salary will be determined by the applicant’s education, experience, knowledge, skills, geo-location and abilities, as well as internal equity and alignment with market data.

Prove follows a market driven compensation philosophy based on geographic location and respective market rates. Job offers will be aligned to location. Please speak with your recruiter if you have questions. Prove defines:

  • Metro 2 - NYC metro area, Seattle metro area, Los Angeles metro area, and the Miami metro area.
  • Metro 3 - all other cities across the domestic United States, with the exception of the San Francisco Bay Area.

Benefits & Perks for FTE Provers:

  • Competitive salaries & Bonus Plan (for eligible roles) and Equity Plan
  • Modern Health for financial, mental, and physical wellness
  • 401(k) Retirement Plan & Match (US Offices) and Local Country Pension (International Offices)
  • Unlimited Vacation and Flexible hours
  • Comprehensive medical benefits for you and your family ❤️
  • Emotional & Physical Wellness – Access to wellness services (EAP & Prove Well-Being Reimbursement)
  • Bottomless snacks & beverages for certain office locations
  • Daily GrubHub stipend for lunch if coming into the office (US Offices)
  • A great place to work and connect with other talented Provers like yourself!

Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Prove we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

Equal Opportunity Employment:

Prove is an equal opportunity employer committed to providing equal employment opportunity for all people regardless of race, color, religion, gender or sexual orientation, age, marital status, national origin, citizenship status, disability, veteran status or other personal characteristics

Privacy & Data Protection:

When you are applying for a job at Prove, we collect and use your personal information in the job application process. To understand more about how Prove uses your personal information, please see our Recruitment Privacy Policy on our website.

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Data Analytics Manager Data Analytics at Headspace

Leads data analytics strategy and complex projects, translating business problems into scalable analytical frameworks and driving data-driven decision-making across the organization.

Lead Posted 8 days ago RemoteFirstJobs Product
What this role involves

About the Manager, Data Analytics at Headspace:

What you will do:

  • Drive significant business outcomes by leading impactful and complex data projects that align with strategic priorities.
  • Define and execute the vision for data analytics, ensuring alignment with company goals and objectives.
  • Provide thought leadership by collaborating with Product, Engineering, Marketing, and Operations to translate complex business problems into scalable analytical frameworks.
  • Recommend and implement actionable insights that drive measurable results and optimize key business metrics.
  • Serve as the organization’s subject matter expert on advanced statistical analysis, experimental design, methodology, and financial impact analysis, ensuring best practices are followed.
  • Guide the team in executing A/B testing strategies, data modeling, and predictive analytics to inform

decision-making.

  • Lead root cause analyses for critical business metrics, crafting structured approaches to identify and address key drivers. Facilitate discussions with senior stakeholders and teams to prioritize and implement optimization strategies that drive efficiency and growth.
  • Architect and implement automation solutions for analytical processes, including experimentation readouts and self-service analytics, improving scalability and efficiency.
  • Drive innovation in reporting and data accessibility to empower stakeholders with real-time insights.
  • Lead the development of high-quality data product requirements, dashboard scopes, and automated

reporting solutions.

  • Build strong partnerships with Data Engineering, Business Intelligence, and other data stakeholders to enhance data infrastructure and accessibility.
  • Partner with Business Intelligence engineering teams to drive both immediate data initiatives and the long-term vision for data-driven reporting and metric frameworks.
  • Advocate for the adoption of best-in-class analytics tools, methodologies, and governance practices.
  • Independently identify opportunities for improvement or growth, initiate projects, and lead them to successful outcomes with measurable impact.
  • Establish and refine analytical processes to ensure consistency, accuracy, and scalability across the organization.
  • Deliver compelling presentations to cross-functional teams and executive leadership, showcasing data-driven insights with clarity and precision.
  • Effectively communicate complex analytical findings in a way that drives strategic decision-making and organizational alignment.
  • Supervise a team of Staff Engineers, Staff/Sr. Data Analysts, and Capacity Planning Sr. Manager.
  • Telecommuting permitted pursuant to company policy.

What you will bring:

Required Skills:

  • Education Requirements: Bachelor’s degree or foreign equivalent in Computer Science, Statistics, Mathematics, Business Analytics, or related quantitative field.
  • Experience Requirements: Five (5) years of experience as a Lead Data Analyst, Lead Business Analyst, Product Data Analyst, Data Scientist, or related occupation.
  • Must have experience with the following: working directly with executive leadership and product leaders to align analytics with strategic goals; analytics focused on customer growth, engagement, and lifecycle optimization; owning and managing data products; big data technologies (Redshift, S3, Databricks, Datalakes, and Spark); and SQL, Python, R, Looker, Tableau, Statistics, Amplitude, Domo, CoreMetrics, Google Analytics, and Excel.)

Location:

We are currently hiring this role remotely in the greater Los Angeles, California area. Candidates must permanently reside in the US full-time.

Pay & Benefits:

The anticipated new hire base salary range for this full-time position is $158,900 - $224,250 + equity + benefits.

Our salary ranges are based on the job, level, and location, and reflect the lowest to highest geographic markets where we are hiring for this role within the United States. Within this range, individual compensation is determined by a candidate’s location as well as a range of factors including but not limited to: unique relevant experience, job-related skills, and education or training.

Your recruiter will provide more details on the specific salary range for your location during the hiring process.

At Headspace, base salary is but one component of our Total Rewards package. We’re proud of our robust package inclusive of: base salary, stock awards, comprehensive healthcare coverage, monthly wellness stipend, retirement savings match, lifetime Headspace membership, generous parental leave, and more. Additional details about our Total Rewards package will be provided during the recruitment process.

About Headspace

Headspace exists to provide every person access to lifelong mental health support. We combine evidence-based content, clinical care, and innovative technology to help millions of members around the world get support that’s effective, personalized, and truly accessible whenever and wherever they need it.

At Headspace, our values aren’t just what we believe, they’re how we work, grow, and make an impact together. We live them daily: Make the Mission Matter, Iterate to Great, Own the Outcome, and Connect with Courage. These values shape our decisions, guide our collaborations, and define our culture. They’re our shared commitment to building a more connected, human-centered team—one that’s redefining how mental health care supports people today and for generations to come.

Why You’ll Love Working Here:

  • A mission that matters—with impact you can see and feel
  • A culture that’s collaborative, inclusive, and grounded in our values
  • The chance to shape what mental health care looks like next
  • Competitive pay and benefits that support your whole self

How we feel about Diversity, Equity, Inclusion and Belonging:

Headspace is committed to bringing together humans from different backgrounds and perspectives, providing employees with a safe and welcoming work environment free of discrimination and harassment. We strive to create a diverse & inclusive environment where everyone can thrive, feel a sense of belonging, and do impactful work together.

As an equal opportunity employer, we prohibit any unlawful discrimination against a job applicant on the basis of their race, color, religion, gender, gender identity, gender expression, sexual orientation, national origin, family or parental status, disability*, age, veteran status, or any other status protected by the laws or regulations in the locations where we operate. We respect the laws enforced by the EEOC and are dedicated to going above and beyond in fostering diversity across our workplace.

*Applicants with disabilities may be entitled to reasonable accommodation under the terms of the Americans with Disabilities Act and certain state or local laws. A reasonable accommodation is a change in the way things are normally done which will ensure an equal employment opportunity without imposing undue hardship on Headspace. Please inform our Talent team by filling out this form if you need any assistance completing any forms or to otherwise participate in the application or interview process.

Headspace participates in the E-Verify Program .

Privacy Statement

All member records are protected according to ourPrivacy Policy. Further, while employees of Headspace (formerly Ginger) cannot access Headspace products/services, they will be offered benefits according to the company’s benefit plan. To ensure we are adhering to best practice and ethical guidelines in the field of mental health, we take care to avoid dual relationships. A dual relationship occurs when a mental health care provider has a second, significantly different relationship with their client in addition to the traditional client-therapist relationship—including, for example, a managerial relationship.

As such, Headspace requests that individuals who have received coaching or clinical services at Headspace wait until their care with Headspace is complete before applying for a position. If someone with a Headspace account is hired for a position, please note their account will be deactivated and they will not be able to use Headspace services for the duration of their employment.

Further, if Headspace cannot find a role that fails to resolve an ethical issue associated with a dual relationship, Headspace may need to take steps to ensure ethical obligations are being adhered to, including a delayed start date or a potential leave of absence. Such steps would be taken to protect both the former member, as well as any relevant individuals from their care team, from impairment, risk of exploitation, or harm.

For how how we will use the personal information you provide as part of the application process, please see: https://www.headspace.com/applicant-notice

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Data Analytics Director Market Access Deal Analytics at Axsome Therapeutics, Inc.

Director leads data analytics and modeling initiatives to support payer strategy, reimbursement optimization, and contracting decisions for pharmaceutical products.

Lead Onsite Posted 19 days ago RemoteFirstJobs Product
What this role involves

Axsome Therapeutics is a biopharmaceutical company leading a new era in the treatment of central nervous system (CNS) conditions. We deliver scientific breakthroughs by identifying critical gaps in care and develop differentiated products with a focus on novel mechanisms of action that enable meaningful advancements in patient outcomes. Our industry-leading neuroscience portfolio includes FDA-approved treatments for major depressive disorder, excessive daytime sleepiness associated with narcolepsy and obstructive sleep apnea, and migraine, and multiple late-stage development programs addressing a broad range of serious neurological and psychiatric conditions that impact over 150 million people in the United States. Together, we are on a mission to solve some of the brain’s biggest problems so patients and their loved ones can flourish. For more information, please visit us at www.axsome.com and follow us on LinkedIn and X.

About This Role

Axsome Therapeutics is seeking a Director, Market Access Deal Analytics to serve as a strategic leader in developing data-driven solutions that inform payer strategy, reimbursement optimization, pricing, and patient access. The ideal candidate will bring deep experience in payor and PBM deal analytics, strong understanding of payor incentives, Medicare and Medicaid reimbursement, understanding of specialty pharmacy, hub, patient services programs, and a pragmatic, action-oriented mindset that connects insights to execution. This position reports to the Senior Director, Pricing and Contracting Strategy.

This role is based at Axsome’s HQ in New York City with an on-site requirement of at least three days per week. We are unable to consider candidates who are looking for fully remote roles.

Job Responsibilities and Duties include, but are not limited to, the following:

  • Conduct robust analytics to support business cases to be presented to Pricing Terms Committee (PTC)

  • Support development on contracting language that supports meeting of business intent

  • Lead analytics strategy to inform payer contracting, coverage optimization, and payer engagement across Axsome’s in-line and pipeline products

  • Conduct claims data analyses [rejections, reversals, abandonment] to understand coverage dynamics, formulary behavior, and their implications on uptake and persistency

  • Design modeling frameworks to guide formulary negotiations, segmentation strategies, and gross-to-net (GTN) investment optimization

  • Build predictive tools to estimate how payer policies and pricing dynamics influence new therapy adoption across CNS specialties

  • Drive integration of payer analytics into National Account pull-through strategy, including actionable field-level insights for Market Access and Field Sales teams

  • Support development of key metrics, and report payer and PBM contract performance to Pricing Committee and Executive Leadership

  • Construct scenario-based forecasting models that simulate the impact of price and access changes on revenue and patient access

  • Monitor formulary positions and their downstream impact on prescribing behavior, conversions, and persistency to inform contract renewal cycles

  • Partner with Finance and GTN teams to continuously refine accruals based on evolving pricing and access dynamics

  • Collaborate closely with Forecasting, Commercial Operations, HEOR, and Market Access Data Science teams to harmonize analytics across functions

  • Embed analytics into pricing and access strategy development, ensuring that all recommendations are grounded in data and aligned to business goals

  • Proactively identify opportunities to improve data infrastructure, automate insight generation, and enhance decision support capabilities

Requirements / Qualifications

  • Bachelor’s degree in Economics, Statistics, Public Health, or related field. Advanced degree (MBA, MPH, PhD) preferred

  • Minimum 10 years in pharmaceutical or healthcare analytics with a focus on market access, pricing, or payer strategy

  • Proven track record in supporting product launches from an access analytics perspective

  • Strong background in CNS therapeutic areas or other specialty/rare disease domains, highly preferred

  • Ability to work on site Monday, Tuesday & Thursday

Experience, Knowledge and Skills

  • In-depth understanding of U.S. payer systems (commercial, Medicare, Medicaid), reimbursement pathways, and formulary dynamics

  • Proficiency in large-scale healthcare datasets (claims, syndicated data sources,  longitudinal data sources)

  • Strong experience in payer contracting analytics, GTN modeling, and assessing ROI on market access investments

  • Expertise in PBM/Payor Contract Language

  • Familiarity with data visualization platforms (e.g., Power BI, Tableau) and cloud-based data ecosystems

  • Ability to develop and validate predictive models using machine learning or regression-based techniques

  • Ability to influence senior stakeholders across Commercial, Access, and Corporate functions

  • Experience managing external vendors, data partners, and cross-functional projects with multiple competing priorities

  • Excellent communicator who can distill technical content into strategic narratives

Salary and Benefits:

The anticipated salary range for this role is $190,000 - $215,000. We encourage candidates of all levels to apply as there may be flexibility on final job title and responsibilities. The salary offer will be based on a variety of factors, including experience, qualifications, internal equity and location. Axsome offers a competitive employment package that includes an annual bonus, significant equity and a generous benefits package.

Axsome is committed to equal employment opportunity and providing reasonable accommodations to applicants with physical and/or mental disabilities. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, gender, sex, age, religion, creed, national origin, sexual orientation, gender identity, ancestry, citizenship, marital status, physical or mental disability, medical condition, veteran status, genetic information, or any other characteristic protected by federal, state, or local law.

Axsome Therapeutics does not accept unsolicited resumes from recruiters or third-party recruitment agencies and will not pay placement fees for unsolicited candidates that are sent to hiring managers, the HR team or other Axsome team members. Only approved vendors who have been explicitly asked to support a specific search will receive access to our Applicant Tracking System to submit candidates for consideration.

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Data Analytics Director, Business Insights (P&C Insurance Personal Lines Planning & Forecasting

Director leading business insights, planning, and forecasting for P&C insurance operations at a Fortune 100 company.

Lead Posted 19 days ago Himalayas
What this role involves
If you’re passionate about helping people protect what matters most to them at a Fortune 100 company with nearly $70 billion in annual sales, as well as innovating and simplifying processes and operations to provide the best customer value, then Nationwide’s Property and Casualty team could be the place for you!
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