Location: United States
Cap-Exempt H-1B Position — No lottery required
**Location** Work from Home **Job Category** Business Strategy and Innovations **Schedule** Days **Work Type** Full time **Department** Artificial Intelligence Product Management Division **Date posted** 04/16/2026 **Job ID** R-94620 ### **Job Summary** Why Geisinger: Geisinger is operationalizing AI at scale across one of the nation's most integrated health systems, moving beyond pilots and proof of concepts to build capabilities that change how care is delivered and how operations run. This role works across clinical, operational, health plan, and pharmacy functions alongside AI product development and organizational leadership to identify and advance the AI opportunities that matter most. This role provides the analytical foundation that makes good AI investment decisions possible, from sizing what is worth building next to supporting the external partnership evaluations that expand Geisinger AI capabilities. Position Summary: This is a role for an analyst who wants their work to drive real strategic decisions, not just report on things after the fact. Embedded within Geisinger AI Discovery and Strategy function, you will build the quantitative case for which AI opportunities deserve investment, size the potential value of what the organization is considering, and provide the analytical grounding that keeps discovery work honest. You will work alongside product managers and organizational leaders across clinical, operational, health plan, and pharmacy domains, and your findings will directly inform what gets built and which partnerships get pursued. ### **Job Duties** **Key Responsibilities:** - Do the portfolio level analysis that tells the discovery team where to focus next, identifying where the biggest clinical and operational gaps exist and which AI opportunity areas have the strongest evidence for investment - Work directly with clinical, operational, health plan, and pharmacy leaders across Geisinger to understand strategic priorities, surface data driven