Provides strategic leadership for enterprise data science, analytics governance, automation, and data enablement across therapeutic areas. Oversees analytics pipelines, data architectures, visualization, AI/ML adoption, regulatory compliance, and clinical data standards. Advises executives, leads cross-functional collaboration, manages analytics teams, drives organizational change, and advances scalable analytical capabilities. Requires extensive experience with large datasets, programming, statistics, data visualization, database concepts, and people management in clinical or digital health settings.

Owns sample management workflows across pharmaceutical development modalities, serving as a technical SME for Appian, Benchling, LIMS, and related data systems. The role gathers requirements, defines data capture standards, develops scientific dashboards and exports, supports digital strategy, mentors team members, and drives adoption of digital tools across drug substance, drug product, analytical, biologics, small-molecule, and vaccine development.

Conduct computational oncology research using statistics, machine learning, AI, and multi-omics data. Analyze NGS, functional genomics, CRISPR, and single-cell datasets; nominate targets, biomarkers, and drug combinations; integrate biological evidence; apply foundation models and LLM-based tools; and collaborate with experimental, engineering, and program teams to support reproducible discovery research.