Associate Vice President of Methods4Insight, Data Foundry
Role details
Job location
Tech stack
Job description
The Head of Methods4Insight will lead the analytical methods and computational science pillar within Data Foundry, directing a team of domain experts spanning cheminformatics, computational structural biology, statistical modeling, and AI/ML. This leader will ensure Lilly has access to the most advanced analytical approaches across all domains critical to molecule discovery, serving both human scientists and autonomous AI agents.
This role combines deep technical breadth with strategic vision. You will maintain awareness of the state-of-the-art across multiple analytical domains-from physics-based molecular modeling to generative AI-and make informed decisions about when to adopt external methods, when to develop novel approaches, and when classical methods outperform sophisticated ones. You will partner with Architecture4Insight to ensure analytical methods are deployed on robust, scalable infrastructure, with Scale4Insight to integrate methods into real-time experimental workflows, and with Preparedness4Insight to embed data quality and governance standards into analytical pipelines by design.
The ideal candidate is a recognized thought leader in computational methods for drug discovery who demonstrates excellent judgment in method selection and application, and has a proven track record delivering analytical insights that accelerate discoveries and improve decisions., * Serve as the strategic leader for analytical methods across Data Foundry, maintaining deep awareness of cutting-edge approaches in cheminformatics, computational structural biology, statistical modeling, mathematical physics, and AI/ML, and establishing Methods4Insight as the authoritative source for guidance on analytical approaches to discovery challenges.
- Build and maintain a portfolio of analytical capabilities spanning classical methods to cutting-edge AI-including QSAR/QSPR modeling, molecular docking, free energy calculations, molecular dynamics, Bayesian experimental design, active learning, deep learning, and generative models-ensuring the right approach is matched to each scientific question.
- Make strategic build-versus-buy-versus-adopt decisions for analytical capabilities, balancing speed of adoption with need for customization, and collaborating with leading analytical teams across Lilly to ensure best practices are shared.
- Proactively identify strategic "data deserts"-areas where Lilly lacks sufficient data to answer critical questions-and develop strategies to fill these gaps through targeted in silico modeling or high-throughput experimental data generation, prioritized by scientific impact and strategic value.
- Establish rigorous frameworks for evaluating and validating analytical methods, including prospective validation protocols and impact metrics that demonstrate decisions influenced, timelines accelerated, and experimental success rates improved.
- Collaborate closely with the Frontier AI group to ensure analytical methods are designed as "agent-ready" capabilities with well-defined APIs, structured inputs/outputs, error handling, and uncertainty quantification for use by autonomous AI agents.
- Collaborate closely with Architecture4Insight, Scale4Insight, and Preparedness4Insight to ensure Methods4Insight analytical capabilities are fully integrated across all Data Foundry pillars and the broader discovery ecosystem.
- Build and lead a team of domain experts, each recognized as a thought leader in their analytical specialty, fostering a culture of intellectual curiosity, continuous learning, and innovation.
- Champion a culture of scientific rigor, reproducibility, and continuous improvement across all analytical workflows.
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 of experience developing, evaluating, and deploying analytical methods for drug discovery, with significant pharmaceutical or biotechnology industry experience.
Additional Preferences:
- Deep expertise in at least one analytical domains with broad understanding across all domains relevant to drug discovery.
- Deep understanding of statistical foundations underlying both classical and modern ML methods.
- Demonstrated thought leadership through publications, conference presentations, or other recognition as a domain expert.
- Demonstrated success leading multidisciplinary computational teams in a matrixed, global organization.
- Breadth across multiple computational disciplines demonstrating versatility and ability to integrate approaches.
- Experience evaluating and adopting external methods, tools, and platforms-demonstrating ability to critically assess new approaches.
- Strong communication and collaboration skills across scientific, technical, and executive stakeholders.
- Track record of driving innovation in analytical methods and enabling new scientific capabilities.
- Passion for mentoring and empowering teams in a fast-paced, mission-driven environment.
Benefits & conditions
In-Office 5 Locations 260K-381K Annually Expert/Leader In-Office 5 Locations 260K-381K Annually Expert/Leader Lead Methods4Insight to define, validate, and deploy analytical and computational methods for molecule discovery. Build/guide a multidisciplinary team, set evaluation frameworks, prioritize build-vs-buy decisions, fill strategic data gaps, and integrate agent-ready AI capabilities across Data Foundry. The summary above was generated by AI, Actual compensation will depend on a candidate's education, experience, skills, and geographic location. The anticipated wage for this position is $259,500 - $380,600
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly's compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
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