Senior Director, AI for Clinical Intelligence & Evidence Breast & Gynaecology

AstraZeneca • Gaithersburg, MD

2d • $203,214 - $304,820 • Hybrid

About The Position

The Senior Director, AI for Clinical Intelligence & Evidence, Breast & Gynaecology leads a multidisciplinary team that generates clinical intelligence and evidence across the Breast & Gynaecology portfolio. The role combines expertise in epidemiology and Real-World Evidence (RWE) with people leadership, strategic prioritisation, and understanding of AI and machine learning to focus the team on high-value questions.

The position partners with drug development teams to translate clinical and portfolio questions into research objectives addressable through real-world data and advanced methods. The role guides scientific approaches and determines where RWE and AI can contribute to evidence supporting drug development and improved patient outcomes.

The role sits within AI for Clinical Intelligence & Evidence, part of AI to Transform Care. The function integrates clinical, trial, and real-world data to support regulatory, HTA, and payer-grade evidence; establish real-time and agentic RWE systems; and generate clinical intelligence for decision-making. The Senior Director also helps develop scalable, enterprise-level capabilities and promotes collaboration across disease-area teams.

Requirements

• Advanced degree (PhD, MPH, MD, or MSc) in Statistics, Epidemiology, Public Health, Data Science, Mathematics, or a related field.
• 10+ years of experience in life sciences or healthcare, with deep expertise in epidemiology and Real-World Evidence generation, including applying RWD to support clinical decision-making.
• Strong experience with health analytics and routinely collected healthcare data, including assessing data sources and approaches for fitness for purpose.
• Experience translating clinical and development questions into research objectives addressable with RWD and appropriate epidemiological and statistical methods, in multidisciplinary teams.
• Experience in quantitative science, such as health outcomes modelling, health economics, or epidemiology, and familiarity with statistical and scripting languages.
• Understanding of Oncology drug development, particularly Phase 3 and beyond, including RWE in clinical trials, patient recruitment, evidence generation, and external or synthetic control approaches.
• Experience with AI/ML methods, or a strong understanding of their principles, strengths, limitations, and appropriate application to Real-World Data.
• Experience with regulatory submissions or HTA dossiers leveraging RWE.
• Proven experience line managing direct reports, developing talent, and building effective multidisciplinary teams.
• Ability to translate complex outputs into clear, decision-ready insights.
• Ability to prioritise strategically, manage competing demands, and adapt team focus and resources as Oncology strategy and portfolio needs evolve.
• Ability to work across clinical, scientific, quantitative, and technology disciplines in a global, matrixed organisation.
• Strong communication and influencing skills, including communicating complex scientific topics, evidence, and trade-offs clearly to senior stakeholders.

Nice To Haves

• Experience within Oncology, particularly Breast and/or Gynaecological cancers.
• Hands-on experience in data science, machine learning, and predictive modelling.
• Familiarity with Bayesian inference, temporal modelling, multimodal modelling, foundation models, and model interpretability and evaluation.
• Experience with clinical text, electronic health records, imaging, or molecular data, including genomics in clinical care or translational medicine.
• Knowledge of clinical data standards, medical terminologies, and healthcare ontologies.
• Experience in late-stage drug development and access, including Phase 3 clinical trial design, biomarkers, safety, endpoints, and regulatory, HTA, or payer interactions.
• Experience developing or applying external or synthetic control arms and other approaches integrating RWD with clinical trials.
• Experience in a patient-care or similar setting, bringing a medical or clinical perspective to RWE generation.
• Experience establishing or managing collaborations with academic institutions, healthcare organisations, technology partners, data providers, or industry consortia.
• Up-to-date knowledge of AI and machine learning developments, with scientific judgement to distinguish meaningful applications from technological hype.

Responsibilities

• Define and evolve the Clinical Intelligence & Evidence strategy for Breast & Gynaecology, aligning scientific priorities and capabilities with Oncology portfolio needs.
• Provide scientific leadership in epidemiology and Real-World Evidence, advising on study designs, analytical methods, and use of routinely collected healthcare data.
• Partner with drug development teams to identify where RWE, AI, and advanced methods can add value and translate clinical and portfolio questions into research objectives.
• Apply Real-World Evidence to support clinical development questions.
• Shape appropriate use of machine learning and AI within RWE, identifying useful opportunities and distinguishing meaningful applications from technological hype.
• Support advanced methods including predictive modelling, patient subtyping, disease progression modelling, temporal modelling, and insight extraction from clinical text and other real-world data.
• Lead and develop a multidisciplinary team by setting objectives, providing feedback and coaching, supporting career development, and fostering an inclusive, collaborative, high-performing environment.
• Prioritise work according to potential impact on the Oncology portfolio and patients, balancing immediate development needs with longer-term scientific and capability priorities.
• Build relationships across drug development, clinical, scientific, data, and AI teams; influence Global Product Teams, matrix teams, and external partners to keep evidence technically rigorous and strategically relevant.
• Collaborate with other Clinical Intelligence & Evidence teams to share expertise, develop common capabilities, and scale valuable AI approaches across therapeutic-area portfolios.
• Work with external organisations, including healthcare organisations, data providers, and research collaborators, to access data, expertise, and capabilities that strengthen evidence generation.
• Advance Real-World Evidence and AI-enabled clinical intelligence through rigorous, clinically meaningful work focused on drug development and patient outcomes.
• Help shape the wider Clinical Intelligence & Evidence operating model, promoting collaboration across disease-area teams and scalable enterprise capabilities.

Benefits

• Short-term incentive bonus opportunity.
• Eligibility to participate in an equity-based long-term incentive program.
• Qualified retirement program, including a 401(k) plan.
• Paid vacation and holidays.
• Paid leaves.
• Health benefits including medical, prescription drug, dental, and vision coverage, subject to applicable plan terms and conditions.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior