Executive Director, AI for Discovery

Executive Director, AI for Discovery Global Locations

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 Executive Director, AI for Discovery within the AI for Science Innovation Unit, you will lead AstraZeneca’s strategy for applying advanced AI and machine learning to accelerate discovery across Oncology andBioPharmaceuticalsR&D. You will drive integrationofcutting-edgeAI approaches into target identification, mechanism-of-action understanding, compound optimization, and early discovery decision-making.

You will guide a global organization and serve as a vertical AI capability that connects Discovery Biology, Chemistry, Translational Medicine, Early Development, and Enterprise AI. You will partner closely with scientific and therapeutic area leadership to deliver AI-enabled insights that improve biological understanding, enhance discovery strategies, and increase probability of technical success across the pipeline.

• Strategic Leadership
• Develop and own AstraZeneca’s enterprise AI strategy for Discovery, spanning target identification/validation, compound optimization, mechanistic modeling, and hypothesis generation.
• Embed AI capabilities across the discovery ecosystem to enable multimodal data integration, mechanistic modeling, and candidate optimization.
• Translate high-level scientific priorities into a clear portfolio of AI-enabled discovery capabilities.
• Guide, partner, and lead strategies and initiatives at the highest levels within AstraZeneca Discovery at SET, EVP, and SVP levels.
• Serve as a member of Discovery leadership teams in both ORD and Bio Pharma R&D.

• Serve as a thought leader and advisor to Discovery Biology, Discovery Chemistry, Translational Medicine, and Therapeutic Area leadership on AI applications.
• Partner with teams to incorporate AI into experimental design, compound selection, mechanistic studies, and early decision-making.
• Foster strong relationships across AI for Science Innovation, Enterprise AI, Data Science, and Therapeutic Areas.

• Define operating models and talent-development paths for a world-class team of AI-fluent discovery scientists and engineers.
• Shape and manage external partnerships with technology providers and academic labs.
• Represent AstraZeneca externally in scientific and regulatory forums.
• Build and lead a high-performing global organization promoting rigor, innovation, and collaboration.
• Lead talent development and succession planning for a team of ~20 direct and indirect reports.

• PhD, MD, or equivalent in computational, biomedical, chemical, or discovery sciences.
• 10-12+ years of experience across discovery science, computational biology, chemistry, or AI/ML in life sciences.
• Track record applying AI to discovery and mechanistic biological challenges.
• Expertise in multimodal data integration, mechanistic modeling, and early discovery analytics.
• Strong scientific publication record in discovery science or AI-driven biology.
• Experience deploying AI/ML solutions in discovery or early research environments.
• Strong literacy across molecular, multimodal, and language foundation models.
• Executive presence with abilityto influence across matrixed organizations.

The annual base salary for this position in the US ranges from $258157,60 - $387236,40. However, base pay offered may vary depending on multiple individualized factors, including market location, job-related…