Data Scientist, Actuarial Health Economics & Payer Modeling

Sprinter Health; San Francisco (CA); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Pre-IPO equity

Medical, dental, and vision plans

Flexible PTO

Parental leave

Job summary

Sprinter Health is seeking a Data Scientist with an actuarial focus to quantify the long-term economic value of home-based care. You will build total-cost-of-care and PMPM projections from claims, assess MLR impact, and defend results to a payer actuaries team.

This hands-on role requires strong SQL and Python or R, plus health-economics modeling experience, and the ability to communicate with non-technical stakeholders.

Qualifications

• Deep experience building actuarial or health-economic models from administrative claims data.
• Experience with total cost of care, PMPM, utilization, trend and risk metrics.
• Ability to defend analyses to payers’ actuaries and translate results for pricing/reserving/bid work.

Responsibilities

• Actuarial & economic modeling: build TCOfC, PMPM, and MLR models from claims data to quantify long-term impact of programs.
• Payer credibility: represent Sprinter with health plans and translate analyses into value narratives for pricing and risk discussions.
• Measurement & rigor: define metrics to prove causal impact and collaborate with Data Science on experimental design.

Skills

Actuarial modeling

Data analysis

Health economics

Tools

Python

R

SQL

Job description

Sprinter Health is seeking a Data Scientist with an actuarial focus to quantify the long-term economic value of home-based care. You will build total-cost-of-care and PMPM projections from claims, assess MLR impact, and defend results to a payer actuaries team.

This hands-on role requires strong SQL and Python or R, plus health-economics modeling experience, and the ability to communicate with non-technical stakeholders.