Healthcare Actuary, Applied ResearcherRole Details- Full-Time
- Office Location - New York City (preferred)
Role OverviewWe are looking for a healthcare actuary with deep expertise in how health systems and medical groups evaluate risk, price contracts, forecast costs, and navigate the shift toward value-based care. We have incredible product-market fit and demand across diverse customer profiles. Executing on this demand requires someone who understands actuarial methodology inside and out - and can translate that expertise into AI-powered systems that scale across hundreds of healthcare organizations.
What You'll DoTo facilitate the development of these systems, you will:
- Develop and deliver subject-matter expertise in healthcare actuarial science to support AI research - including risk stratification, financial forecasting, payer mix analysis, and reimbursement modeling
- Build forward-looking forecasting models for healthcare organizations: cost trend projections, utilization forecasts, revenue forecasts under different payer and contract scenarios, and budget variance prediction
- Develop frameworks for evaluating value-based care performance, including shared savings/losses, capitation economics, ACO financial benchmarking, and risk corridor analysis
- Model healthcare pricing and risk, including rate-setting assumptions, medical loss ratios, utilization patterns, and population health cost drivers
- Build revenue cycle analytics models covering denial rate drivers, net collection forecasting, contractual adjustment analysis, and payer contract performance
- Work closely with our engineering, product, and design teams to operationalize actuarial logic - including forecasting engines - into production code and AI Agents
- Support risk-bearing entity analysis - helping health systems understand their exposure across commercial, Medicare Advantage, Medicaid managed care, and direct contracting arrangements
- Partner directly with customers to validate assumptions, stress-test forecasts, and translate complex actuarial and risk concepts for finance audiences
- Build proprietary benchmarks and datasets to evaluate models and AI Agents against real-world actuarial tasks - including cost trending, risk scoring, reserve estimation, and contract modeling
What You Have- ASA or FSA designation (or near-credentialed with a clear path)
- 5-10 years of experience in healthcare actuarial work - health plan pricing, provider risk, Medicare/Medicaid, commercial lines, or value-based care arrangements
- Proven experience building financial forecasts in healthcare: cost trends, utilization projections, revenue modeling, or reserve development
- Deep understanding of risk-based payment models: capitation, shared savings, bundled payments, risk adjustment (HCC/RAF scoring), and stop-loss structures
- Strong command of claims data, utilization metrics, cost of care analytics, and healthcare reimbursement mechanics
- Ability to effectively communicate with a variety of internal and external stakeholders and translate complex actuarial problems between finance, product, and engineering teams
- Ability to define positive outcomes in situations with underspecified success criteria
- Deep intellectual curiosity and eagerness to learn across domains - particularly at the intersection of actuarial science and AI
- Willingness and desire to do work in the trenches - e.g., grading hundreds of model-generated forecasts, breaking down thousands of claims files, stress-testing risk models against real-world standards. Getting AI to do actuary-level healthcare finance work requires a lot of things that look like actuary-level healthcare finance work
Nice to Have- Experience on the provider side - working with health system finance teams evaluating risk-bearing contracts, not just payer-side reserving
- Familiarity with SQL, Python, or other data tools
- Background in building scenario-based or Monte Carlo-style forecasting models
- Background in Medicare Advantage bid development, MSSP/ACO REACH benchmarking, or Medicaid managed care rate-setting
- Prior exposure to AI/ML concepts or prompt engineering
- Experience at a high-growth startup
Anticipated compensation: $175,000 - $250,000 with Equity
