Staff Data Scientist, Healthcare Economics

Pomelo Care is the leading virtual medical practice for women and children, providing care across pregnancy, postpartum, pediatrics, menopause, and perimenopause. We combine proactive, 24/7 clinical care with technology that helps us reach patients earlier, identify risks sooner, and deliver personalized care throughout their journey. Our team includes clinicians, technologists, operators, and problem-solvers working together to make high-quality care more accessible for families nationwide.

About The Role

Your north star:

Own how Pomelo's clinical and economic impact is measured, proven, and presented - to our payer partners, to external partners, and in published research. We're looking for a data scientist experienced in healthcare outcomes assessment or program evaluation to join our Health Economics team. Trustworthy, actionable data plays a critical role in Pomelo's mission to improve pregnancy outcomes.

This role goes far beyond reporting. The analyses you produce feed directly into renewal and expansion negotiations with national payers, shape how new risk-based and value-based offerings are structured, and become the evidence base we publish. You'll inherit a strong foundation of established methods and infrastructure, and you'll regularly need to build on it to answer novel questions, explore new methodologies, and communicate results to audiences with very different backgrounds.

You will have direct influence on how we measure impact and tell our story externally.

What you'll do

• Own the question as well as the analysis. Take large, ambiguous mandates and break them into definitions, assumptions, and key questions to align stakeholders
• Architect and execute analyses that assess the outcomes of Pomelo Care's programs in a scalable, repeatable way. Where existing approaches don't reach, you'll extend them or build something new, and stand behind those choices under scrutiny
• Lead Pomelo's technical engagement with external partners: presenting directly, aligning on methodology and parameters, and building credibility with evaluation teams
• Drive our evidence strategy end to end: partner-facing reporting, conference presentations, and peer-reviewed publications
• Build data tables, pipelines, and dashboards that combine diverse health data sources and make insights accessible across teams
• Identify opportunities to scale and automate insights in partnership with the data and analytics engineering teams
• Serve as Pomelo's expert on statistics and health economics: define the methodologies we use for evaluation, mentor other data scientists, and guide where we invest technically
• Who you are
• A collaborative problem solver and analytic thinker who is focused on driving impact, and excited to work at a startup.
• 6+ years professional experience developing statistical models to answer complex healthcare problems using varied techniques (e.g., propensity score matching, linear and logistic regressions, k-means clustering, difference-in-differences, decision trees)
• Experience with cost of care or clinical outcomes target setting at a payer, managed care organization, integrated delivery network, value-based care provider, or healthcare consulting firm
• Experience presenting statistical analyses to external stakeholders with varied technical expertise
• Proficient in Python or R and SQL
• You do your best work when the goal is ambiguous. You are comfortable telling others "here's what I recommend and why" rather than waiting to be told what to analyze
• You have the technical depth to run a publication-grade evaluation and the judgment to know when a scrappy proof-of-concept is the better call. You never lose sight of why the work matters to the business
• Excellent written and verbal communicator, comfortable across technical and non-technical audiences
• Formal training in statistics, econometrics, or actuarial science
• Experience with risk-based or value-based contracting, including opportunity sizing and ROI modeling
• Experience with medical claims data
• Peer-reviewed publications in health outcomes or health economics
• Experience with data dashboarding or visualization (e.g., Looker, Tableau, Metabase)
• Experience working with dbt