Lead Data Scientist

Lead Data Scientist

Our customers is a growing health benefits company. The company is hiring a Lead Data Scientist to own its predictive cost models that will forecast future healthcare spend for employer populations and turn that into pricing decisions leadership can act on. The ideal candidate has hands-on experience with claims data and has built pricing models within the healthcare space. This is part of a larger modernization for this candidate to deliver additional models and help build internal AI products.

Responsibilities

• Lead development of predictive models that forecast next-year healthcare cost and utilization for employer groups
• Build modeling approaches that hold up with incomplete or open claims data, where missing claims don't mean missing care
• Develop and validate PMPM, trend, and high-cost claimant methodologies
• Incorporate risk adjustment and scoring (HCC, ACG, DxCG, or similar) into pricing models
• Translate model output into clear recommendations for underwriting, finance, and executive stakeholders
• Set modeling standards, validation practices, and documentation for a small data team
• Work with data engineering to define data requirements and close quality gaps

Requirements

• 8+ years in data science or predictive analytics, with recent hands-on work on medical and Rx claims
• Proven experience building cost or utilization prediction models in group underwriting, stop-loss, payer, TPA, or health analytics consulting
• Fluency in PMPM, member months, IBNR/claims lag, allowed vs. paid, and risk scoring
• Strong Python or R, plus SQL, with the ability to explain models to non-technical leaders
• Experience leading or mentoring other data scientists preferred