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

Role: Director Clinical Intelligence & Evidence Cardiovascular Renal and Metabolism

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 highquality realworld 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 realworld 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 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 toClinical Development Regulatory and other cross-functional stakeholderson the use of real-world data and evidence to address critical questions.
• Partner with asset teams to shape evidence strategies supporting key pipeline decisions includingdisease understanding indication prioritization patient segmentation comparator strategy endpoint feasibility and protocol optimization.

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.

AIEnabled 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 ofreusable tools analytical pipelines standards and workflowsin 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 AIenabled 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 regulatoryrelevant 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 privacypreserving data environments.
• Experience in analysing multimodal RWD to support decision making
• Cardiovascular Renal and Metabolic experience.

Next Steps

Are you ready to step up and take ownership of your work solutions for the business and your personal career development Apply now and join us in our mission to bring life-changing medicines to people!

Where can I find out more

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