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Sprinter Health is reimagining home-based healthcare delivery, having supported 2M+ patients across 22 states with 130,000+ in-home visits and a 92 NPS. The company has raised $125M from top-tier investors including a16z, General Catalyst, GV, and Accel.
You will be the first data scientist in an actuarial-focused role, responsible for quantifying the long-term economic value of Sprinter's interventions to health plans. This is a hands-on, applied position where you build models rather than write memos.
Key responsibilities include:
- Build total-cost-of-care, PMPM (per-member-per-month), and medical-loss-ratio (MLR) models from claims data to project how Sprinter's interventions change cost, utilization, and risk over multi-year horizons.
- Produce model outputs and tables that payer actuaries can directly integrate into their pricing, reserving, and bid work.
- Represent Sprinter in MLR and medical-economics conversations with health plans, defending analyses to their actuarial teams.
- Define rigorous measurement frameworks to distinguish causal impact from correlation, partnering with the data science team on experimental design.
- Turn analysis into value narratives for quality, risk, and finance teams; support commercial pricing and sales with actuarial evidence.
Required qualifications:
- Deep experience building actuarial or health-economic models from administrative claims (total cost of care, PMPM, utilization, trend, risk adjustment).
- Strong command of MLR, risk adjustment, and multi-year projection methods, with judgment about their limits.
- Proficiency in SQL and Python or R; ability to build and own models end-to-end.
- Ability to communicate with actuaries and medical-economics teams, and explain analysis to non-technical stakeholders.
- Solid understanding of causal inference and its limitations.
Preferred experience:
- Actuarial credentials (ASA, FSA, MAAA) or exam progress (not required).
- Payer-side, value-based-care, or risk-bearing experience; familiarity with Medicare Advantage, Stars, and risk adjustment.
- Track record of producing analysis that customers or partners integrated into their own pricing or reserving.
- Fluency with AI coding assistants (Claude Code, Cursor) in development workflow.
The company operates on a hybrid schedule: Monday–Thursday in-office, Fridays work-from-anywhere. Daily lunch is provided and shared with the team. Benefits include meaningful pre-IPO equity, 100% employer-paid medical/dental/vision, flexible PTO, 401(k) match, 16-week parental leave (birthing parent), HSA/FSA, life insurance, disability coverage, and annual learning stipend.
