Director​/Sr​/Exec Dir - Applied Intelligence Discovery; AI4D

Organization Overview

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our more than 50,000 employees around the globe take on complex challenges to discover and deliver life‑changing medicines, strengthen how health is understood and managed, and support the communities we serve.

This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

We are building something unprecedented — an AI foundation that will fundamentally change how drug discovery research is conducted.

The Executive Director of Applied Intelligence for Discovery (AI4D) will own the technical vision and execution for AI capabilities that enable discovery researchers across therapeutic areas to work in entirely new ways. You will partner with senior leaders across the organization to align these capabilities with research priorities, secure the resources to deliver on the vision, and drive adoption that turns platform potential into scientific impact.

You will define the strategic direction for our AI and data science capabilities, ensuring they deliver measurable research acceleration while maintaining the rigor required in regulated drug development.

This role exists to drive a specific transformation: from discovery research that is computationally supported to discovery research that is computationally driven. That means building platforms where AI doesn’t just accelerate existing workflows but enables fundamentally new ones.

• Build and lead a multidisciplinary team spanning data science, ML engineering, and scientific software development
• Set technical vision and roadmap for AI/ML platforms serving discovery research, aligning capabilities with enterprise priorities
• Own the full platform lifecycle — from identifying and integrating new AI capabilities to sun setting legacy solutions, optimizing for overall portfolio performance as research priorities evolve
• Guide architecture decisions for end‑to‑end ML workflows: data pipelines, feature engineering, model development, deployment, and monitoring
• Serve as executive champion for AI capabilities, articulating value to senior partners and influencing resource allocation
• Identify, establish, and manage strategic partnerships with technology providers and research institutions to expand platform capabilities
• Drive adoption of MLOps practices that enable reproducible, automated, and compliant AI development at scale
• Partner with technology and therapeutic area leaders to envision and complete high‑impact AI applications and translate research requirements into platform capabilities
• Work across organizational boundaries in a complex matrixed environment to align platform strategy with scientific priorities

• Bachelor’s degree, Master’s degree or PhD in Computer Science, Data Science, Computational Biology, or related field
• Minimum 15 years experience in AI/ML or data science

• Proven track record driving AI/ML from concept to scaled deployment in complex matrixed organizations
• 5+ years leading teams with a preference for building them to scale
• Deep expertise in modern ML frameworks, MLOps practices, and cloud platforms (AWS, Azure, GCP)
• Demonstrated track record of driving AI/ML capabilities from concept through scaled deployment in complex, matrixed organizations — with evidence of measurable impact on business outcomes, not just model performance
• Ability to translate between scientific research questions and technical solutions
• Experience navigating cross‑functional dynamics and influencing without direct authority
• Experience in pharmaceutical, life sciences, or healthcare industries
• Track record managing external technology partnerships and vendor relationships
• Platform architecture background — you think in systems and portfolios, not features and projects

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