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About the Role
We are seeking a Data Scientist with an actuarial focus to quantify the long-term economic value of Sprinter's services. This role involves building models to project costs, impacts, and risks, and presenting these findings in a format usable by payer actuarial teams for pricing, reserving, and bid work. It is a hands-on, applied position where you will define best practices.
Responsibilities
- Build total-cost-of-care, PMPM, and MLR models from claims data to quantify the long-term impact of Sprinter’s programs.
- Project how interventions change cost, utilization, and risk over multi-year horizons, and quantify the uncertainty around those projections.
- Produce model outputs and tables that a payer’s actuaries can plug directly into their pricing, reserving, and bid work.
- Represent Sprinter in MLR and medical-economics conversations with health plans; go toe-to-toe with their actuaries.
- Turn analysis into value narratives that quality, risk, and finance teams can act on.
- Help the commercial team price and sell Sprinter’s impact on an actuarial basis.
- Define the yardstick for whether an intervention actually changed cost and outcomes, not just whether it correlated with them.
- Partner with Data Science on the causal and experimental design behind those measurements.
- Bring an honest view of the line between value we can prove and value we can only assert.
Requirements
- Deep experience building actuarial or health-economic models from administrative claims: total cost of care, PMPM, utilization, trend, and risk.
- Command of the methods payers price on — MLR, risk adjustment, and multi-year projection — and the judgment to know their limits.
- Strong SQL and Python or R, with the ability to build and own your models end to end.
- Ability to hold your own with actuaries and medical-economics teams, and to explain the analysis to non-technical stakeholders.
- Honesty about causal inference — what a given design can and cannot claim.
Skills
- Actuarial modeling
- Health economics
- Total cost of care modeling
- PMPM modeling
- MLR modeling
- Utilization projection
- Trend analysis
- Risk modeling
- Pricing methods
- Risk adjustment
- Multi-year projection
- SQL
- Python
- R
- Causal inference
- AI coding assistants
Location
- Hybrid
Work Type
- Hybrid
- Full-time
Experience Level
- Mid-level
- Senior-level
Education Level
- Actuarial credentials (ASA, FSA, MAAA, or actuarial exam progress) are welcome but not required.
Benefits
- Meaningful pre-IPO equity
- Medical, dental, and vision plans 100% paid for you and your dependents
- Flexible PTO + 10 paid holidays per year
- 401(k) with match
- 16-week parental leave policy for birthing parent, 8 weeks for all other parents
- HSA + FSA contributions
- Life insurance, plus short and long-term disability coverage
- Free daily lunch in-office
- Annual learning stipend
About the Company
- Sprinter Health is reimagining how people access care by bringing it directly to their homes.
- Nearly 30% of patients in the U.S. skip preventive or chronic care simply because they can’t get to a doctor’s office.
- For many, the ER becomes their first touchpoint with the healthcare system—driving over $300B in avoidable costs every year.
- By using the same technologies that power leading marketplace and last-mile platforms, we deliver care where people are, especially those who need it most.
- So far, we’ve supported more than 2 million patients across 22 states, completed 130,000+ in-home visits, and maintained a 92 NPS.
- Our team of clinicians, technologists, and operators have raised over $125M to date investors like a16z, General Catalyst, GV, and Accel and enjoy multi-year runway.