Director, Clinical Intelligence & Evidence – Cardiovascular, Renal and Metabolism
Hybrid · Cambridge, England, United Kingdom
Job Summary
Director, Clinical Intelligence & Evidence – Cardiovascular, Renal and Metabolism leads the strategy and execution of high-quality real-world evidence programs across the CVRM portfolio. Responsibilities include guiding evidence generation strategies for key pipeline decisions, providing senior scientific leadership for observational research and advanced evidence generation, driving AI/ML adoption to accelerate study delivery and standardise phenotyping and endpoint definition, and developing reusable analytical tools and pipelines. The role involves partnering with Clinical Development, Regulatory and cross-functional teams, contributing to publications and thought leadership, and engaging externally at scientific and regulatory forums. Requires advanced degree in a related field, deep RWE expertise, strong data science skills (Python, R, SQL), and proven leadership of multiple workstreams; experience in cardiovascular, renal, and metabolic domains is highly valued.
Required Qualifications
- Advanced degree (PhD or MSc) in epidemiology, biostatistics, data science, or a related discipline
- Excellent stakeholder engagement and influencing skills across scientific and clinical functions
- Substantial experience leading real-world evidence (RWE) generation within pharmaceutical or biotech R&D
- Deep expertise in observational study design, causal inference, and regulatory-relevant RWE
- In-depth knowledge of Real-World Data assets (claims, EHRs, registries)
- Demonstrated experience applying advanced analytical methods, including AI or machine learning, to address questions in drug development and evidence generation
- Strong technical fluency in Python, R, and SQL
- Proven ability to lead multiple concurrent workstreams in a matrixed, cross-functional environment
- Cardiovascular, Renal and Metabolic experience
- Familiarity with federated analytics and privacy-preserving data environments
- Experience in analysing multimodal RWD to support decision making
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