Associate Vice President - Methods4Insight, Data Foundry
Eli Lilly and Company
2 months ago
On-site
Louisville, CO
$259,500 - $380,600 USD yearly
IT
Position Summary
- Lead the analytical methods and computational science pillar within Data Foundry, directing a team of domain experts in cheminformatics, computational structural biology, statistical modeling, and AI/ML.
- Ensure Lilly has access to advanced analytical approaches across molecule discovery, for both human scientists and autonomous AI agents.
- Partner with Architecture4Insight, Scale4Insight, and Preparedness4Insight to deploy analytical methods on robust infrastructure, integrate into real-time experimental workflows, and embed data quality/governance into analytical pipelines.
Responsibilities
- Serve as the strategic leader for analytical methods across Data Foundry and establish Methods4Insight as the authoritative source for analytical guidance.
- Build and maintain a portfolio of analytical capabilities (e.g., QSAR/QSPR, docking, free energy calculations, molecular dynamics, Bayesian experimental design, active learning, deep learning, generative models).
- Make build-versus-buy-versus-adopt decisions for analytical capabilities and collaborate to share best practices.
- Identify strategic “data deserts” and develop strategies to fill gaps via in silico modeling or high-throughput experimental data generation.
- Establish rigorous evaluation/validation frameworks, including prospective validation protocols and impact metrics.
- Collaborate with the Frontier AI group to make analytical methods “agent-ready” (APIs, inputs/outputs, error handling, uncertainty quantification).
- Collaborate with Architecture4Insight, Scale4Insight, and Preparedness4Insight to integrate Methods4Insight across Data Foundry and the discovery ecosystem.
- Build and lead a team of domain experts; foster intellectual curiosity, continuous learning, and innovation.
- Champion scientific rigor, reproducibility, and continuous improvement.
Basic Requirements
- Ph.D. in Cheminformatics, Computational Biology, Biophysics, Applied Mathematics, Computer Science, Statistics, or related quantitative field with strong application to drug discovery.
- 15+ years developing, evaluating, and deploying analytical methods for drug discovery; significant pharmaceutical or biotechnology industry experience.
Additional Preferences
- Deep expertise in at least one analytical domain with broad understanding across drug discovery-relevant domains.
- Strong statistical foundations for classical and modern ML methods.
- Thought leadership (publications, conference presentations, or similar recognition).
- Proven success leading multidisciplinary computational teams in a global, matrixed organization.
- Breadth across computational disciplines; ability to integrate approaches.
- Experience evaluating/adopting external methods, tools, and platforms.
- Strong communication and collaboration across scientific, technical, and executive stakeholders.
- Track record driving innovation in analytical methods and enabling new scientific capabilities.
- Passion for mentoring and empowering teams in a fast-paced, mission-driven environment.
Additional Information
- Travel: requires travel; work environment is office-based.
- Benefits: eligibility for company bonus and comprehensive benefits (401(k), pension, vacation, medical/dental/vision/prescription coverage, flexible benefits, life insurance, time off/leave benefits, well-being benefits).
- Lead the analytical methods and computational science pillar within Data Foundry, directing a team of domain experts in cheminformatics, computational structural biology, statistical modeling, and AI/ML.
- Ensure Lilly has access to advanced analytical approaches across molecule discovery, for both human scientists and autonomous AI agents.
- Partner with Architecture4Insight, Scale4Insight, and Preparedness4Insight to deploy analytical methods on robust infrastructure, integrate into real-time experimental workflows, and embed data quality/governance into analytical pipelines.
Responsibilities
- Serve as the strategic leader for analytical methods across Data Foundry and establish Methods4Insight as the authoritative source for analytical guidance.
- Build and maintain a portfolio of analytical capabilities (e.g., QSAR/QSPR, docking, free energy calculations, molecular dynamics, Bayesian experimental design, active learning, deep learning, generative models).
- Make build-versus-buy-versus-adopt decisions for analytical capabilities and collaborate to share best practices.
- Identify strategic “data deserts” and develop strategies to fill gaps via in silico modeling or high-throughput experimental data generation.
- Establish rigorous evaluation/validation frameworks, including prospective validation protocols and impact metrics.
- Collaborate with the Frontier AI group to make analytical methods “agent-ready” (APIs, inputs/outputs, error handling, uncertainty quantification).
- Collaborate with Architecture4Insight, Scale4Insight, and Preparedness4Insight to integrate Methods4Insight across Data Foundry and the discovery ecosystem.
- Build and lead a team of domain experts; foster intellectual curiosity, continuous learning, and innovation.
- Champion scientific rigor, reproducibility, and continuous improvement.
Basic Requirements
- Ph.D. in Cheminformatics, Computational Biology, Biophysics, Applied Mathematics, Computer Science, Statistics, or related quantitative field with strong application to drug discovery.
- 15+ years developing, evaluating, and deploying analytical methods for drug discovery; significant pharmaceutical or biotechnology industry experience.
Additional Preferences
- Deep expertise in at least one analytical domain with broad understanding across drug discovery-relevant domains.
- Strong statistical foundations for classical and modern ML methods.
- Thought leadership (publications, conference presentations, or similar recognition).
- Proven success leading multidisciplinary computational teams in a global, matrixed organization.
- Breadth across computational disciplines; ability to integrate approaches.
- Experience evaluating/adopting external methods, tools, and platforms.
- Strong communication and collaboration across scientific, technical, and executive stakeholders.
- Track record driving innovation in analytical methods and enabling new scientific capabilities.
- Passion for mentoring and empowering teams in a fast-paced, mission-driven environment.
Additional Information
- Travel: requires travel; work environment is office-based.
- Benefits: eligibility for company bonus and comprehensive benefits (401(k), pension, vacation, medical/dental/vision/prescription coverage, flexible benefits, life insurance, time off/leave benefits, well-being benefits).