AI Lead: Drug Discovery and Development

Job Title: AI Lead:
Drug Discovery and Development

Location: Boston Seaport, USA

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.

As AstraZeneca continues to put patients at the forefront of our mission, we are excited for our move to Kendall Square/Cambridge in 2026. Find out more information here:
Kendall Square Press Release

Alexion is seeking a visionary AI leader to shape and implement the AI strategy across our R&D organization, spanning early research, preclinical work, and clinical development. This role will partner closely with R&D teams to translate scientific challenges into actionable AI opportunities, accelerate pipeline productivity, enable AI‑driven solutions that accelerate innovation, enhance scientific rigor, and advance transformative medicines for patients with rare diseases.

You will lead the design, development, and adoption of sophisticated AI/ML capabilities that elevate target discovery, optimize trial design and execution, strengthen data‑driven decision making, and unlock new scientific insights across the R&D lifecycle. This role blends deep technical expertise with strong product thinking, scientific competence, and exceptional partner leadership.

• AI Strategy & Portfolio: Identify and prioritize business‑aligned AI opportunities and define the multi‑year AI strategy and roadmap. Govern the portfolio from proof‑of‑concept through validation to scaled products, with clear stage gates, success metrics, and value tracking.
• Ownership & Delivery: Act as the product owner for AI solutions (e.g., target , compound optimization, translational and clinical decision support). Set problem statements, adoption thresholds, and benefits realization plans; oversee delivery with internal teams and partners.
• Business Interface & Partnerships: Serve as the primary interface between R&D teams, data scientists, and external AI partners. Translate scientific and operational needs into AI solutions. Evaluate buy, build, partner options and manage vendors/consortia.
• Workflow Integration & Change: Lead the integration of AI into business workflows, data systems, and SOPs. Motivate change management and adoption programs, including partner engagement, training, communications, super‑user networks, feedback loops, and human‑in‑the‑loop controls.
• Data & Platforms: Partner with the Head of Data and Tech teams to enable access to high‑quality, well‑governed research and clinical data, promote FAIR principles, and influence platform architecture and MLOps/LLMOps considerations to scale AI responsibly.
• Governance, GxP & Responsible AI: Ensure AI solutions meet GxP, data integrity, privacy and audit requirements. Establish practices for model validation, bias/robustness testing, explain‑ability, documentation, model monitoring, performance SLAs, and inspection readiness.
• Impact & Communication: Define OKRs/KPIs tied to R&D outcomes (e.g., hit/lead success rates, cycle time reduction, protocol optimization, enrollment speed, cost avoidance, risk detection). Track and communicate progress, impact, and value to R&D and executive leadership with clear narratives and evidence.
• Talent & Culture: Build and nurture a cross‑functional network of super‑users and AI champions; set standards and procedures. Foster a culture of scientific rigor, product thinking, innovation, and measurable impact; promote agile ways of working across Alexion.

• Education: Advanced degree preferred (MS/PhD in life sciences or quantitative fields; or…