Data Scientist, Actuarial

Sprinter Health • San Francisco, CA

4d • Hybrid

About The Position

We’re looking for a Data Scientist with an actuarial focus to quantify the long-term economic value of what Sprinter does. When we tell a health plan that finding and treating disease in the home lowers their cost of care over time, someone has to turn that claim into numbers the plan’s actuaries will trust. That is this role. You will build the models yourself: total-cost-of-care and per-member-per-month (PMPM) projections from claims, medical-loss-ratio (MLR) impact, and a defensible account of how Sprinter’s interventions change cost and risk over a multi-year horizon. You will package those outputs so a customer’s actuarial team can plug them straight into their pricing, reserving, and bid work. This is a hands-on, applied role, not an advisory one — we would rather you build the table than write a memo about it. The ideal candidate is a quantitative scientist who thinks like an actuary and is comfortable talking actuary-to-actuary with a payer’s medical-economics team. Formal actuarial credentials are welcome but not required; we care that you can do the work and defend it. This is a first-of-function role; you will define what good looks like.

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.

Nice To Haves

• Actuarial credentials (ASA, FSA, MAAA, or actuarial exam progress) — welcome but not required.
• Payer-side, value-based-care, or risk-bearing experience; familiarity with Medicare Advantage, Stars, and risk adjustment.
• Experience producing analysis that a customer or partner built into their own pricing or reserving.
• Fluency with AI coding assistants (e.g., Claude Code, Cursor) in your day-to-day development workflow.

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.

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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed