Responsibilities:
- Build and lead the Real World Evidence (RWE) Innovation Center (RWDIC): define mission/governance/KPIs/operating model; set RWD engagement vision (partnership models, AI workflows, enterprise data infrastructure); act as enterprise authority on RWD strategy and standards.
- Build end-to-end RWE data capability: lead end-to-end data connectivity architecture for Global Medical; identify/evaluate/build TA-level RWD landscape (EMR/EHR, claims, registries, specialty/global sources); bridge MEG teams to the Unified Data Layer; drive continuous innovation in data sources, study design paradigms, AI/digital tools.
- Ensure enterprise cross-functional connectivity: liaise with WWTA, HEOR, Clinical Development, Market Access, Commercial, and BI&T/Data Analytics; represent Medical RWD priorities in roadmaps/governance/AI platform decisions; activate existing data sources and prevent duplication; steward partnerships with RWD vendors/academics/epidemiological networks; connect evidence generation to enterprise AI/LLM capabilities.
- Provide scientific expertise for NIS/epidemiology/advanced designs: standardize RWD-first study planning; maintain RWDIC knowledge base; advise on non-traditional designs.
- Build capability and training: create RWD training curriculum; lead RWD Community of Practice and knowledge management (playbooks, landscape summaries, design/acquisition guidance).
Qualifications:
- Degree in Epidemiology, Biostatistics, Health Sciences, or related RWE field (PhD or equivalent preferred).
- 10+ years in RWE/epidemiology/health data science in pharma/biotech/clinical settings.
- Deep expertise in RWD ecosystems (claims, EMR/EHR, registries, global specialty sources) and experience building/managing TA/enterprise data access programs.
- Track record building new functions/capabilities in complex orgs.
- Experience applying AI and digital analytics to RWE workflows.
- Strong executive presence and communication.