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Salary: USD 220,000 - 250,000 / annual
Pomelo Care is a virtual medical practice for women and children, delivering care across pregnancy, postpartum, pediatrics, menopause, and perimenopause. The company combines 24/7 clinical care with technology to identify risks early and deliver personalized care nationwide.
You will own how Pomelo's clinical and economic impact is measured, proven, and presented to payer partners, external stakeholders, and in peer-reviewed publications. This role goes beyond reporting: your analyses directly inform renewal and expansion negotiations with national payers, shape the structure of new risk-based and value-based offerings, and become the evidence base for published research.
Key responsibilities include:
- Taking large, ambiguous mandates and breaking them into clear definitions, assumptions, and key questions to align stakeholders
- Architecting and executing scalable, repeatable analyses that assess program outcomes; extending or building new methodologies where existing approaches fall short
- Leading technical engagement with external partners through direct presentations, methodology alignment, and credibility-building with evaluation teams
- Driving the evidence strategy end-to-end: partner-facing reporting, conference presentations, and peer-reviewed publications
- Building data tables, pipelines, and dashboards that combine diverse health data sources and make insights accessible across teams
- Identifying opportunities to scale and automate insights in partnership with data and analytics engineering teams
- Serving as Pomelo's expert on statistics and health economics: defining evaluation methodologies, mentoring other data scientists, and guiding technical investment decisions
You are a collaborative problem solver excited to work at a startup, comfortable with ambiguity, and able to recommend analyses with clear reasoning. You balance the ability to run publication-grade evaluations with judgment about when a scrappy proof-of-concept is the better call, never losing sight of business impact. You communicate effectively across technical and non-technical audiences.
Requirements:
- 6+ years professional experience developing statistical models to answer complex healthcare problems using varied techniques (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
- Proficiency in Python or R
- Proficiency in SQL
- Ability to work effectively with ambiguous goals and recommend analyses independently
- Excellent written and verbal communication skills across technical and non-technical audiences
Bonus qualifications:
- 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 tools (Looker, Tableau, Metabase)
- Experience with dbt
