develop predictive models, risk and profitability logic, and scenario/forecast frameworks that translate claims, contract terms, and market signals into the numbers our deal teams act on
partner with underwriters, pricing actuaries, and finance to translate business questions into testable code — pricing calculators, P&L tools, recurring forecasts, and the rule engines underneath them
balance a long-running model build, a quick-turn analysis for a sales leader, and a recurring reporting cycle in the same week

3+ years of hands-on experience delivering data science or advanced analytics in a regulated, numbers-heavy environment (healthcare, PBM, insurance, banking, or similar)
Production-quality Python (or R) — not throwaway notebooks — and advanced SQL across complex, multi-source datasets
Solid statistical fundamentals: regression, classification, clustering, time-series forecasting, hypothesis testing
Working knowledge of cloud data platforms (GCP, Azure, AWS, or Databricks/Snowflake) and PySpark or equivalent for large-scale data work
Comfort with financial concepts (margin, loss ratio, premium, retention) — or proven ability to pick them up fast
Low-maintenance, high-output: takes context and runs, flags own mistakes early, frames every analysis around the decision it supports

medical, dental, and vision coverage
paid time off
retirement savings options
wellness programs
comprehensive benefits package designed to support the physical, emotional, and financial well-being of colleagues and their families

Decision Scientist – Product

Key skills