Director, Data Science: Medical, Special Investigations, and Programs (MSP) Claims Data Science team

Description Our Medical, Special Investigations, and Programs (MSP) Claims Data Science team is hiring a Director, Data Science to support growing business demand in Medical and Workers' Compensation Claims. This is a senior individual contributor role for an experienced, execution-focused data scientist who can independently partner with stakeholders to identify, prioritize, and build ML and AI capabilities in a space with a minimal existing data science footprint.A successful candidate in this role will partner closely with leaders in Claims and delivery partners in Insights & Solutions and Technology to establish and execute on a roadmap of foundational Machine Learning and AI capabilities to enhance adjuster workflows and related supporting processes (e.g., Quality Improvement). While this role will begin as an Individual Contributor, it is expected that this leader will build a team around them as they establish their execution strategy.This role may have in-office requirements depending on candidate locationCandidates who live within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week. Otherwise, this role is remote with occasional travel.What you'll do: Partner closely with leaders in Claims and other delivery partners (Insights & Solutions, Technology, and Enterprise Data) to identify AI/ML opportunities and create a delivery roadmap that prioritizes the most impactful work. Design, build, and iterate on Machine Learning and Generative & Agentic AI capabilities which deliver real business value for adjusters in Medical and Workers' Compensation claims. Collaborate with our partner teams to architect & deliver end-to-end intelligent systems integrating machine learning, LLMs, RAG pipelines, agentic workflows, and structured/unstructured claims data to solve real business problems. Apply strong software engineering and ML/AI Ops practices, in