Senior Director, Head of AI for Clinical Development, Late Oncology

Were 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: youll 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 - youll have the platform (and sponsorship) to make it real.

About AISI

AI Science & Innovation (AISI) sits at the centre of AstraZenecas R&D AI transformation. Our remit is to build buy and deliver the AI models and agents that change pipeline outcomes across discovery translational science biomarkers and clinical development.

Role Overview

AstraZeneca is building a world-class AI capability for Clinical Development within AISI to accelerate the design conduct and analysis of confirmatory trials across our Oncology and BioPharmaceuticals pipeline. Phase III is where assets meet the regulatory and label-evidence bar and where AI must be useful defensible and audit-ready. We are hiring the Head of AI for Clinical Development Late Oncology to lead the science and the team that turns AI promise into real-world improvements in late phase clinical trials including trial enrichment external evidence label-relevant endpoints and submission-ready insight.

This is one of the hardest and highest impact challenges in AI for healthcare. The playbook for AI at this stage will be developed in the next two to three years. We partner closely with domain experts in clinical development regulatory and biometrics to advance the science of clinical development to bring better treatments to patients faster while adhering to the highest evidentiary standards. Were hiring someone who sees that as the reason to come because they are committed to using AI for real measurable improvement in healthcare.

AI for clinical development is a field in motion. Foundation models multimodal learning agentic systems and causal AI advance rapidly and the regulatory and methodological frameworks around them are evolving in parallel. Youll pick the right bets among rapidly changing options and continuously absorb new methods as the field redefines whats possible. Comfort with ambiguity and an instinct to learn in public are core to the role.

The AI for Clinical Development function is being built from the ground up and youll help define how AstraZeneca does AI for late-phase trials. Expect an outsized voice with regulators scientific consortia and external partners during the narrow window when the rules of the road for AI in pivotal evidence are being written.

We hire for learning agility and technical excellence. The strongest candidate is the person who learns fast is comfortable with ambiguity prototypes early fails forward and partners credibly across communities (ML clinical biostatistics regulatory). Were seeking a scientist with the leadership technical depth and curiosity to develop adapt and apply the most advanced methods in AI including multimodal foundation models agentic AI generative patient models to late-phase clinical decision-making and who can sit across from clinical-development teams to translate their priorities into actionable innovative and evaluable AI solutions.

Above all this is a role where the science matters. Every model you ship will eventually touch a trial that decides whether a patient gets a better therapy. That is the bar we hold ourselves to and the bar we hire to.

What youll do

• Lead AstraZenecas AI R&D for Phase III programs across oncology leveraging and integrating AI solutions across the late development program.
• Lead a team of AI researchers and engineers to leverage and integrate AI solutions across late oncology clinical development.
• Develop and evaluate AI methods for innovative trial design (e.g. prognostic risk modelling predictive enrichment AI-driven stratification sample-size and power optimisation and biomarker-defined population strategy).
• Lead innovative approaches to analyze and quality control real-time clinical trial data from late phase trials.
• Develop and evaluate predictive models including AI-based analysis of real-world evidence for Phase III trials (e.g. external control arm methodology predictive and progrnostic models generative patient trajectory models).
• Develop and evaluate AI methods for multimodal label-relevant endpoints imaging-based response digital pathology ePRO and digital biomarkers surrogate-to-OS modelling and for label-shaping analyses (subgroup discovery individual treatment-effect estimation).
• Partner with the Late Oncology Clinical Development and Study Teams to embed AI and AI Strategy into study design and decision-making.
• Partner with Regulatory teams to develop AI-enabled development standards and evidence that meet late-phase regulatory requirements.
• Work closely with the Heads of Early Oncology and BPRD Clinical AI and the Head of Late BPRD Clinical AI to develop innovative AI strategies to guide early- to late-phase decision-making.
• Contribute to developing the AI for Clinical Development teams unified reusable and end-to-end strategies for AI method development evaluation monitoring and oversight.
• Contribute the AI evidence component to regulatory submission packages and the AI scientific and methodological voice on late-phase regulatory engagements.
• Represent AstraZeneca externally in industry forums scientific consortia and peer-reviewed venues.
• Serve as a thought partner for AISI and AI for Clinical Development leadership.
• Recruit mentor and lead a team of approximately five AI scientists and engineers as a player-coach who is hands-on with code models and submission-relevant analyses while building a high-performing team that keeps up-to-date with the latest advances in frontier AI models and agents.
  

Essential for the role

• PhD in Computer Science Machine Learning Computational Biomedical Sciences Biomedical Informatics Biostatistics or a closely related computational discipline with a strong hands-on computational track record. Alternatively MD (or equivalent clinical degree) with significant demonstrated hands-on and leadership experience in computer science/machine learning preferably with post-doctoral training or other advanced training in computer science informatics or data science.
• Minimum 8 years of combined experience across AI/ML method development and clinical development research with demonstrated impact on late phase trial design and/or decision-making.
• Excellent software engineering skills: Python PyTorch Hugging Face cloud platforms (e.g. AWS Azure GCP) and modern LLM tooling.
• Expertise in sandboxing containerization VM infrastructure and/or distributed systems.
• Current hands-on computational expertise peer-reviewed publications in top-tier conferences and/journals and shipped code in clinical AI computational drug development and/or biomedical machine learning. Comfort writing code reviewing model implementations and reproducing results.
• Strong experience in generative and non-generative AI benchmarking and evaluation across clinical and/or biomedical settings.
• Deep familiarity with modern AI methods relevant to confirmatory late clinical development: foundation models (including clinical and multimodal) agentic systems generative patient models / digital twins longitudinal/time-series modelling causal inference and AI methods for safety and pharmacovigilance.
• Knowledge of confirmatory trial design and conduct and the evidentiary bar that AI in pivotal evidence must clear.
• Demonstrated track record of translating AI methods into applications that inform clinical and/or biomedical decisions including prospective evaluation deployment or contribution to submission-relevant evidence.
• Demonstrated scientific leadership: mentoring trainees leading multi-author projects and running a small team overseeing multiple projects.
• Excellent written and verbal communication able to translate technical findings for clinical regulatory and executive audiences.

Desirable for the role

• Direct industry experience in late-phase Oncology late-phase BioPharm or confirmatory clinical development within a pharmaceutical or biotech R&D environment.
• Direct experience contributing to FDA EMA PMDA or MHRA submissions especially submissions involving AI/ML methods external controls digital twins or AI-augmented adaptive designs.
• Experience with hybrid and external-control designs and the AI capability layer that supports them.
• Prior FDA EMA or PMDA engagement on AI methodology complex innovative trial design or AI/ML qualification opinions.
• First- or last-author publications at top ML venues (NeurIPS ICML ICLR *CL) and/or top clinical and biomedical journals.
• Open-source contributions workshop organisation or standards-body participation.
  

Office Working Requirements

When we put unexpected teams in the same room we unleash bold thinking with the power to inspire life-changing -person working gives us the platform we need to connect work at pace and challenge perceptions. Thats why we work on average a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

The annual base pay for this position ranges from $-Annual USD. Base pay offered may vary depending on multiple individualized factors including market location job-related knowledge skills and addition our positions offer a short-term incentive bonus opportunity; eligibility toparticipatein our equity-based long-term incentive program. Benefits offered include a qualified retirement program 401(k) plan; paid vacation and holidays; paid leaves; and health benefits including medical prescription drug dental and vision coveragein accordance withtheterms and conditions of the applicable plans.

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