Design and execute end-to-end studies using state-of-the-art frameworks: causal inference, g-computation, target trial emulation, and counterfactual modeling
Collaborate with Portfolio Heads and Global Program Teams (GPTs) to translate user needs into high-impact deliverables
Define data dependencies, establish progress reporting, and justify budgets/resources
Implement Deep Learning pipelines for omics data, biomarkers, or multimodal datasets
Develop disease progression models and longitudinal forecasting
Oversee development of R/Python packages and decision-support tools for clinical teams
Represent the organization before the FDA and EMA for integrating RWE into regulatory submission dossiers

PhD in Health Sciences, Epidemiology, Biostatistics, or a related quantitative field
Minimum 5 years of experience within a pharmaceutical company or a CRO
Demonstrated expertise in the use of RWE from M0 through Phase III
Advanced expertise in causal inference, machine learning, deep learning, and modern data science tools (R/Python)

Lead Data Scientist – RWE, Causal Inference

Key skills