Senior Director, Machine Learning & AI (BPD)

Role purpose   AstraZeneca's bold ambition is to be a pioneer in science, lead in our disease areas and transform patient outcomes — and by 2030, to deliver 20 new medicines and industry ‑ leading growth. Biologics are central to that ambition, and Biopharmaceutical Development (BPD) is the R&D function that turns biologic candidates into medicines.  BPD develops the cell lines, bioprocesses, formulations,  devices  and analytical methods  needed to advance biologic medicines through clinical development and approv al  where they can improve the lives of  patient s . As the portfolio grows in scale and complexity, BPD is increasingly adopting a Predict ‑ First CMC approach: FAIR data at source, greater use of modelling and digital twins, and AI-enabled tools that help scientists find knowledge, make decisions and create regulatory content more efficiently.   The Senior Director, Machine Learning & AI leads the ML & AI team within BPD: a multidisciplinary group of specialists spanning data science, AI and data engineering, and applied machine learning research. The role is accountable for translating BPD's  Predict First  ambition into a coherent AI strategy and portfolio roadmap that transforms emerging technologies and promising ideas into trusted, scalable capabilities that deliver measurable scientific and business value. The Senior Director defines the ML & AI strategy for BPD, owns delivery of the AI portfolio within the digital transformation roadmap, and serves as BPD's senior technical interface with Enterprise AI and R&D IT. The role  is responsible for   establishing  a framework that rapidly tests and  demonstrates  value through proof-of-concepts ( PoCs ), accelerates adoption through iterative delivery, and enables the scaling of successful AI solutions across BPD.   In addition, the Senior Director partners closely with Robotics & Automation, Informatics, Digital Transformation, Enterprise AI, and R&D IT teams to identify opportunities where ML & AI can enhance scientific, operational, and business outcomes and to integrate AI capabilities into products, platforms, and workflows across BPD   (e .g .  P hysical  A I) . The role provides strategic leadership on the data foundations required to enable AI at scale, including data architecture, governance, engineering, and platform capabilities, ensuring that high-quality, accessible, and trusted data can support advanced analytics, machine learning, and AI solutions across the enterprise.   Success in this role requires a balance of strategic leadership and technical credibility. The Senior Director will shape investment decisions,  build organisational capability, drive adoption across BPD , influence senior stakeholders across BPD and the enterprise, and provide the technical judgement needed to guide delivery and manage risk.   Key accountabilities   Strategy and portfolio   Define and  maintain  BPD’s multi-year ML&AI strategy, aligned with  a  Predict ‑First  CMC  organisation , the BPD digital transformation roadmap and AZ’s AI30 ambitions.   Be accountable for the BPD AI portfolio across the four pillars: AI Foundations & Platforms, Knowledge Management, Modelling & Digital Twins, and Submission & Report Authoring.   Set portfolio priorities across in-flight, self-funded and proposed initiatives, making clear, evidence-based recommendations on when to build, buy, partner, pause or stop.   Technical leadership   Provide senior technical oversight of model strategy, evaluation and deployment across predictive ML, mechanistic and hybrid models, protein sequence and structure models, knowledge graphs,  RAG  and agentic architectures.   Set practical engineering standards for the team, including reproducibility, model risk management,  MLOps , evaluation  frameworks  and human-in-the-loop approaches for  GxP -adjacent use cases.   Chair or lead technical review of the highest-risk or highest-value deliverables, ensuring decisions are well  evidenced  and risks are visible to the right governance forums.   Team leadership   Lead  and   develop   a  high-performing  ML &AI team of data scientists and AI/data engineers, growing capability and reach through permanent hires, secondments, PDRAs and vendor partnerships.   Create the operating model,  ownership  and delivery discipline needed for a small specialist team to have enterprise-level impact.   Support AI training and culture change across BPD, helping scientists use AI well rather than simply  use  it more.   Cross‑functional delivery   Work  with modelling/AI,  digitalisation  and robotics transformation leads to  align  investment, dependencies and delivery plans across AI,  data  and automation.   Partner with R&D  IT  so enterprise platforms meet BPD’s scientific needs, and BPD requirements are visible in strategic platform roadmaps.   Serve as BPD’s senior technical voice into Enterprise AI: adopt enterprise capability where it fits, escalate gaps, and shape shared offerings where BPD should not rebuild common capability   Work closely with CMC Statistics, Informatics & Software Engineering, and Robotics & Automation Development  colleagues  so that ML&AI outputs sit on sound statistical, software and laboratory  foundations. Build  Physical AI as an emerging BPD capability by partnering with Robotics & Automation, Informatics, Digital Transformation, Enterprise AI and R&D IT to connect ML&AI models, agents and decision-support tools with laboratory automation, instrumentation and closed-loop experimental workflows.   Governance,  compliance  and risk   Ensure BPD’s AI work aligns with AZ AI governance, data governance, information  security  and  GxP  expectations, as well as emerging external regulatory guidance on AI in CMC.   Contribute to AZ's regulatory advocacy on AI in CMC where BPD's experience is directly relevant ( e.g.  via the CMC Strategy Board and PMF AI in CMC Working Group).   Be