Lead the scientific development of agentic AI frameworks for discovering prognostic and predictive models in oncology, integrating LLM orchestration with translational science. Architect 'deep agents' for hypothesis generation, experimental design, and multimodal ML using foundation models. Innovate scientific methodology, develop predictive models and causal inference frameworks, and scale scientific discovery.

Director of Epidemiology & Methodological Innovation to lead high-impact research for biopharma partners, focusing on developing and validating novel epidemiological methods using multimodal datasets (clinical, molecular/genomic) and applying causal inference and machine learning techniques. This role involves client-facing strategy, scientific thought leadership, and bridging data science with productization, with a strong emphasis on regulatory-grade insights for drug development.