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Director - Scientific Data Preparedness, Data Foundry

Job in South San Francisco, San Mateo County, California, 94083, USA
Listing for: 100 Eli Lilly and Company
Full Time position
Listed on 2026-10-20
Job specializations:
  • IT/Tech
    Data Engineering, Information & Knowledge Management
Salary/Wage Range or Industry Benchmark: 177000 - 282000 USD Yearly USD 177000.00 282000.00 YEAR
Job Description & How to Apply Below
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 over 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.

At Lilly, we unite caring with discovery to make life better for people around the world.

Position Summary

We are seeking a Senior Director, Scientific Data Preparedness to lead efforts to strengthen the foundations that enable effective use and reuse of scientific data across scientific workflows. The role will establish strategies and practices for data harmonization, metadata and semantic standards, information flow modeling, AI readiness, and integration with Lilly’s enterprise data ecosystem. As part of Architecture4

Insight, this leader will partner closely with Methods4

Insight and Scale4

Insight and engage broadly across Lilly’s scientific and technology organizations to ensure scientific data is prepared to support computational, analytical, and AI-enabled discovery. This role combines team and capability leadership with hands‑on technical engagement and requires a player‑coach who can build and develop teams, influence strategy, and drive execution across a complex scientific and technology landscape.

Key Responsibilities
  • Capability & Team Leadership Build, develop, and coach the team responsible for Scientific Data Preparedness. Establish capability roadmaps, investment priorities, and operating mechanisms. Serve as a senior member of the Architecture4

    Insight leadership team.
  • Scientific Data Harmonization Define the strategy for harmonizing scientific data and metadata across Molecular Discovery. Establish standards that improve interoperability, data quality, and reuse. Partner with data architecture and platform teams to enable a consistent scientific information ecosystem.
  • Information Flow & AI Readiness Define end-to-end information flow models across scientific processes, systems, and data products. Develop frameworks and assessment approaches for scientific data and AI readiness. Identify and prioritize opportunities to improve data accessibility and readiness for AI-enabled use.
  • Enterprise Integration & Stewardship Shape and advance integration of discovery data assets with Lilly’s enterprise data environment. Establish stewardship practices and accountability models for critical scientific information. Partner with enterprise technology and data organizations to align standards, platforms, and governance processes.
  • Player-Coach Leadership Provide hands‑on leadership for strategic Scientific Data Preparedness initiatives. Guide and develop teams and technical leaders through complex scientific data and information challenges. Serve as a trusted advisor to scientific, technical, and business stakeholders.
Basic Requirements
  • BS or higher degree in Computer Science, Data Science, Bioinformatics, Computational Biology, Information Science, or related STEM field.
  • Ph.D. with 6+ years, M.S. with 8+ years, or B.S. with 10+ years of relevant experience.
  • Demonstrated experience leading complex scientific data, information management, data integration, or digital transformation initiatives.
  • Demonstrated leadership in defining and delivering AI-ready scientific data products, with hands‑on experience applying ontologies, metadata standards, and data…
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