Senior Principal Data Scientist, Enterprise AI

ENGAGEMENT OVERVIEW Role: Senior Principal Data Scientist, Enterprise AI Location: Hybrid — 3 days/week onsite in Indianapolis, IN Duration: 6 months minimum, strong likelihood of extension Degree Required: Master of Science or PhD — no exceptions ABOUT THE ROLE This is a senior, highly strategic AI position within Lilly's Enterprise AI group, with scope across the full organization: molecular discovery, genomics, clinical development, manufacturing, supply chain, Finance, HR, and IT. This is not a pure data scientist or pure ML engineer role. Lilly is looking for a rare combination of deep domain expertise, advanced statistical modeling, and production-level ML engineering. The emphasis is on domain expertise, paired with either data science or ML engineering depth. Candidates who bring all three are strongly preferred. The team works on foundational model initiatives applied to pharma and enterprise datasets, similar in class to work done at leading AI research organizations. IDEAL BACKGROUND COMBINATIONS • ChemE undergrad + PhD in Data Science • Clinical or biostatistics expert with strong ML engineering depth • Manufacturing SME turned AI leader • Computational biologist who builds production ML systems KEY REQUIREMENTS • PhD or MS required, paired with 8-12+ years in advanced analytics or AI • Expert Python skills • Proven experience deploying ML models into production (MLOps) • Background in regulated or complex scientific environments • Executive-level communication skills — this is a visible, cross-functional leadership role, not a back-room modeling position • Deep domain expertise in at least one area: Chemical Engineering, Clinical, Genomics, or Manufacturing Sciences • ML engineering and production-level software capabilities strongly preferred RESPONSIBILITIES • Lead and execute advanced data science projects across enterprise functions • Perform statistical analysis and develop innovative data strategies aligned to business outcomes • Design and deliver data visualizations and actionable insights for executive audiences • Collaborate across cross-functional teams including molecular discovery, manufacturing, clinical, and enterprise functions • Contribute to foundational model development applied to pharma and enterprise datasets • Serve as a strategic thought partner on AI-driven decision-making