Medical Director, AI Innovation and Validation, Global Patient Safety

Job Title: Medical Director, AI Innovation and Validation, Global Patient Safety
Location: New York City, NY

At AstraZeneca, we pride ourselves on crafting a collaborative culture that champions knowledge-sharing, ambitious thinking and innovation – ultimately providing employees with the opportunity to work across teams, functions and even the globe.

Recognizing the importance of individualized flexibility, our ways of working allow employees to balance personal and work commitments while ensuring we continue to create a strong culture of collaboration and teamwork by engaging face‑to‑face in our offices 3 days a week
. Our head office is purposely designed with collaboration in mind, providing space where teams can come together to strategize, brainstorm and connect on key projects.

Our dedication to sustainability is also central to our culture and part of what makes AstraZeneca a great place to work. We know the health of people, the planet and our business are interconnected which is why we’re taking ambitious action to tackle some of the biggest challenges of our time, from climate change to access to healthcare and disease prevention.

The Medical Director will provide experienced clinical oversight for the design, validation, and implementation of AI‑driven solutions within Global Patient Safety. This physician leadership role is critical in guiding AstraZeneca's strategy for employing Artificial Intelligence to transform Patient Safety and especially its direct application to clinical safety, transforming Patient Safety’s strategic contribution to clinical development.

You would be responsible for guiding the adoption of AI into all aspects of Patient Safety, demonstrating robust validation of AI tools applied to Patient Safety, and ensuring all AI applications meet the highest standards of medical accuracy, ethical integrity, and regulatory compliance. The role involves shaping the responsible adoption of sophisticated AI, including generative technologies, to enhance pharmacovigilance capabilities such as case processing, safety surveillance, and signal detection as well as clinical assessment of safety cases, case series, and toxicity management and mitigation strategies.

Success hinges on deep medical expertise, a thorough understanding of the AI ecosystem in Patient Safety, and strategic collaboration with internal cross‑functional partners (including Patient Safety, R&DS, IT, Clinical Development, Regulatory Affairs) and proactive engagement with Health Authorities, all to ultimately enhance patient health and safety.

• Clinical Leadership & AI Strategy in Patient Safety:
  • Provide expert medical leadership and strategic direction for the integration of AI technologies within patient safety and pharmacovigilance processes.
  • Champion the ethical and responsible identification, evaluation, and adoption of innovative AI technologies, including generative AI, to improve the efficiency, accuracy, and depth of patient safety insights.
  • Translate complex medical and patient safety requirements into clear objectives for AI development and application, ensuring clinical relevance and utility.
  • Stay abreast of advancements in AI in medicine, regulatory guidance on AI in healthcare, and industry best practices, translating these into actionable strategies for Patient Safety.
• Clinical Validation Framework & AI Governance:
  • Lead the development, implementation, and continuous refinement of a comprehensive clinical validation framework for AI/ML applications in Patient Safety. This includes defining medical performance standards, bias assessment from a clinical perspective, and ensuring generalizability to relevant patient populations.
  • Lead all aspects of the rigorous clinical assessment and validation of AI solutions (both internal and external), ensuring they are medically sound, safe for their intended use, and adhere to global pharmacovigilance regulations (e.g., GVP) and evolving standards for AI in healthcare.
  • Establish and oversee governance processes for the AI lifecycle from a clinical perspective, including input into design, defining appropriate human oversight,…