Director, Clinical Intelligence & Evidence – Cardiovascular, Renal and Metabolism in Cambridge

Location: Cambridge UK

Salary: Competitive + Excellent Benefits

At AstraZeneca, make a meaningful impact that brings real benefits to society. By applying your knowledge of data, you will help to redefine our industry and ultimately save lives. Work with experts who share a common goal: to accelerate the potential of medicines and the science of tomorrow.

The Director, Clinical Intelligence & Evidence is a senior scientific and strategic leader responsible for delivering high‑quality, real‑world evidence (RWE) across the Cardiovascular, Renal and Metabolism (CVRM) portfolio. The role operates at the intersection of epidemiology, advanced analytics, artificial intelligence (AI), biostatistics and pharmaceutical drug development, translating complex real‑world and clinical data into evidence that informs clinical development. A central expectation of the role combines deep technical expertise with strategic thinking and stakeholder management. This role requires experience and understanding of applied use of AI and machine learning to accelerate RWE studies, standardise analytical approaches, and develop scalable tools that improve efficiency, reproducibility, and impact of evidence generation across the organisation. In addition, the ability to architect evidence generation strategies at the disease area level across clinical development stakeholders.

Key Responsibilities

• Strategic Advisory and Clinical Partnership: Serve as a senior strategic advisor to Clinical Development, Regulatory, and other cross‑functional stakeholders on the use of real‑world data and evidence to address critical questions. Partner with asset teams to shape evidence strategies supporting key pipeline decisions, including disease understanding, indication prioritisation, patient segmentation, comparator strategy, endpoint feasibility, and protocol optimisation.
• Scientific & Methodological Leadership: Provide senior scientific leadership for observational research and advanced evidence generation, ensuring work is rigorous, transparent, reproducible, and fit for purpose. Lead the application of advanced methods including target trial emulation, comparative effectiveness research, causal inference, external control arms, longitudinal modelling, phenotyping, predictive analytics, and multimodal data integration, as appropriate to the question and decision context.
• AI‑Enabled Evidence Generation: Lead the adoption of AI and machine learning in RWE, focusing on accelerating study delivery, automating and standardising phenotyping and endpoint definition, and enabling scalable analytical workflows. Drive the development of reusable tools, analytical pipelines, standards, and workflows in partnership with cross‑functional teams. Evaluate emerging methods and technologies to determine where they can deliver meaningful scientific and operational value.
• People, Standards & Capability Building: Provide scientific leadership, coaching, and development to epidemiologists, biostatisticians, programmers, and data scientists. Drive standardisation of methods, analytical approaches, and quality standards, embedding AI where it delivers meaningful efficiency or quality gains.
• External Engagement & Thought Leadership: Represent the organisation at scientific, regulatory, and policy forums. Contribute to publications and thought leadership in RWE methodology and AI‑enabled evidence generation.

Experience & Expertise

Essential:

• 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 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, such as claims, EHRs, registries.
• Demonstrated experience applying advanced analytical methods, including AI or machine learning where relevant, 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.

Desirable:

• Experience developing reusable analytical tools or platforms.
• Familiarity with federated analytics and privacy‑preserving data environments.
• Experience in analysing multimodal RWD to support decision making.
• Cardiovascular, Renal and Metabolic experience.

Date Posted: 15-Jun-2026

Closing Date: 29-Jun-2026

Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.