Senior Director MMAI & Outcome Prediction – AI for Precision Health

AstraZeneca • Gaithersburg, MD

32d

About The Position

We're building a connected, end-to-end Enterprise AI engine - uniting data foundations, AI technology, process reinvention, and business-facing AI to accelerate results across the whole value chain. Success depends on being exceptional connectors: you'll actively leverage existing capabilities, celebrate and promote reuse, export breakthrough ideas across geographies and functions, and obsess over scaling impact rather than building in isolation. If you thrive in high-collaboration environments where your role is to turn complex, cross-functional problems into reusable, enterprise-wide capabilities - and where the measure of success is adoption and scale, not just innovation - you'll have the platform (and sponsorship) to make it real.
As Senior Director, Multimodal AI & Outcome Prediction within Enterprise AI – AI to Transform Care at AstraZeneca, you will lead the scientific translation of multimodal artificial intelligence and foundation model advances into clinically actionable capabilities across Oncology and BioPharma. Working in close collaboration with Enterprise AI, R&D teams, and AI for Science Innovation (AISI), you will drive the development, reinforcement, and validation of multimodal predictive and diagnostic systems integrating radiology, digital pathology, multi-omics (genomics, transcriptomics, proteomics), molecular diagnostics, clinical trial datasets, real-world electronic health records and claims, and longitudinal patient signals including digital biomarkers. Your work will enable the discovery and validation of AI-derived multimodal biomarkers and computational disease taxonomies that improve early diagnosis, refine disease stratification, support companion and AI-enabled diagnostic strategies, identify comorbidities, and guide treatment selection and responder identification. By applying advanced representation learning, outcome modelling, and survival analytics, you will translate multimodal intelligence into clinical development impact through trial enrichment, patient identification, endpoint optimisation, and deeper reanalysis of clinical trial data. In parallel, you will help reinforce foundation models using AstraZeneca’s multimodal trial and real-world datasets, creating continuous learning systems that connect discovery, development, diagnostics, and real-world outcomes across the product lifecycle. The role will also establish enterprise scientific standards for multimodal AI, including validation frameworks, cross-site robustness, regulatory-grade evidence generation, and performance monitoring, ensuring that AI-enabled diagnostic and predictive models can be trusted, scaled, and deployed to improve patient outcomes and accelerate precision medicine across the portfolio.

Requirements

• Advanced degree (Master’s or PhD) in a relevant field such as Biomedical Engineering, Data Science, Computational Biology, Bioinformatics, Digital Health, or Artificial Intelligence.
• + 5 years proven experience leading or contributing to AI-enabled medical or biological projects, such as biomarker discovery, digital pathology, patient stratification, clinical decision support, or disease modeling
• Recognized expertise in multimodal AI applied to Oncology and BioPharma, with demonstrated impact in outcome prediction, computational diagnostics, or precision medicine strategy.
• Deep hands-on mastery of advanced machine learning methodologies including:
• Multimodal representation learning integrating radiology, digital pathology, spatial and bulk omics, molecular diagnostics, digital biomarkers, clinical trials, and real-world data
• Survival modelling, dynamic time-to-event prediction, and competing risk frameworks
• Causal inference methodologies including propensity modeling, marginal structural models, uplift modelling, and treatment effect heterogeneity analysis
• Construction and validation of synthetic and external control arms using real-world evidence
• Development and validation of prognostic and predictive biomarkers across development phases
• Advanced risk stratification, patient subtyping, clustering, and disease trajectory modelling
• Longitudinal modelling of disease evolution and treatment response
• Strong expertise in computational imaging, high-dimensional omics integration, and multimodal feature fusion architectures.
• Proven experience defining validation strategies aligned with regulatory-grade evidence standards, including reproducibility frameworks, cross-site generalisability, bias mitigation, robustness testing, and model lifecycle monitoring.
• In-depth understanding of regulatory and compliance frameworks governing AI in healthcare, including medical device pathways, AI governance, transparency requirements, and data privacy regulations.
• Ability to critically dissect external AI architectures, data provenance, validation methodology, and scalability claims.
• Extensive experience working with large-scale, heterogeneous healthcare datasets including EHR, claims, imaging repositories, genomic platforms, molecular diagnostic datasets, and global clinical trial databases.
• Clinical, Development, and Access Fluency
• Strong scientific grounding in Oncology biology and clinical development, with the ability to connect modelling outputs to therapeutic mechanisms and development strategy.
• Advanced understanding of clinical trial design, enrichment strategies, endpoint optimisation, and evidence package construction.
• Solid knowledge of Market Access principles, value-based healthcare frameworks, and payer evidence requirements.
• Familiarity with companion diagnostics development and precision medicine strategy integration.
• Working knowledge of compliance and legal frameworks relevant to AI-enabled diagnostic and predictive tools.
• Systems and Digital Infrastructure Mastery
• Deep understanding of healthcare data ecosystems and enterprise platforms, including EMR, CTMS, EDC, imaging systems, molecular data systems, and real-world data infrastructures.
• Experience deploying AI models within real-world clinical workflows and complex enterprise environments.
• Strong grasp of scalable AI infrastructure, data architecture principles, and model deployment constraints.
• Leadership and Enterprise Impact
• Demonstrated track record leading large-scale digital health or AI transformation programs with measurable clinical and economic impact.
• Shown ability to shape global strategy and drive adoption across complex, matrixed, multinational organisations.
• Experience building and sustaining high-value external partnerships across academia, technology, diagnostics, and data ecosystems.
• Ability to translate complex computational concepts into clear strategic implications for senior leadership, regulators, clinicians, and payers.
• Entrepreneurial mindset with experience operating in innovation-driven or start-up-like environments.
• High level of integrity, scientific rigor, and credibility, with the ability to influence at executive level.
• Motivated by delivering scientifically robust digital innovation that materially improves patient outcomes and treatment experience.

Responsibilities

• Scientific Leadership in Multimodal AI and Computational Diagnostics
• Advance Diagnostic Innovation and Computational Disease Stratification
• Transform Clinical Development Through Predictive Intelligence
• Reinforce Foundation Models with Clinical and Real-World Data
• Integrate Clinical Trials and Real-World Evidence into Continuous Learning Systems
• Establish Enterprise Standards for Multimodal AI Validation and Governance
• Bridge R&D, Diagnostics, and Transform Care Initiatives
• Develop Strategic External Partnerships in AI and Diagnostics
• Drive Cross-Functional Collaboration and Strategic Alignment
• Elevate Organisational Capability in AI-Driven Precision Medicine

Benefits

• qualified retirement program [401(k) plan]
• paid vacation and holidays
• paid leaves
• health benefits including medical, prescription drug, dental, and vision coverage

What This Job Offers

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