Director - Scientific Data Preparedness, Data Foundry

US, San Francisco CA

Pay: $177,000–281,600/yearAnnual period assumed — pay source
Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is $177,000 - $281,600 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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Work setting: Not stated
Employment: Full-time — employment source
Employment type in the employer’s listing: Full time
From the employer’s posting

What you’ll work on

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.

As part of Architecture4Insight, this leader will partner closely with Methods4Insight and Scale4Insight and engage broadly across Lilly’s scientific and technology organizations to ensure scientific data is prepared to support computational, analytical, and AI-enabled discovery.

Build and coach the Scientific Data Preparedness team and set its roadmap
Define strategy for harmonizing scientific data and metadata across Molecular Discovery
Define end-to-end information flow models across scientific processes and systems
Shape integration of discovery data with Lilly's enterprise data environment
Establish stewardship practices and accountability models for critical scientific information

From the employer’s posting

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 Architecture4Insight, this leader will partner closely with Methods4Insight and Scale4Insight and engage broadly across Lilly’s scientific and technology organizations to ensure scientific data is prepared to support computational, analytical, and AI-enabled discovery.

Build, develop, and coach the team responsible for Scientific Data Preparedness.

Define the strategy for harmonizing scientific data and metadata across Molecular Discovery.

Define end-to-end information flow models across scientific processes, systems, and data products.

Shape and advance integration of discovery data assets with Lilly’s enterprise data environment.

Establish stewardship practices and accountability models for critical scientific information.

What you’ll bring

All qualifications

Core 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 governance policies to make data trusted, interoperable, and reusable.

Preferred experience

Experience in pharmaceutical, biotechnology, life sciences, or research-intensive environments.
Expertise in scientific data management, harmonization, metadata, governance, information architecture, or AI/data readiness.

Qualification wording

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 governance policies to make data trusted, interoperable, and reusable.

Experience in pharmaceutical, biotechnology, life sciences, or research-intensive environments.

Expertise in scientific data management, harmonization, metadata, governance, information architecture, or AI/data readiness.

Education & alternatives

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.

- 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.

Posting record

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Actively hiringFirst seen by us 7 days ago, still listed, and not a repost of an earlier listing.

Status in our records: Live
First seen by us: Oct 16, 2026 · 7 days ago
Recorded sightings: 23
Last seen by us: Oct 23, 2026

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Your next step

Have your resume and examples of relevant work ready.
Check the listed location, eligibility and core experience before starting.

Complete your application on lilly.wd115.myworkdayjobs.com. The employer’s form will show what is required.

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Job description

View original posting ↗

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.

Overview

At Lilly, we unite caring with discovery to make life better for people around the world. Lilly Small Molecule Discovery applies leading science and technology to discover and advance new medicines.

Discovery Technology & Platforms (DTP) accelerates molecule discovery through advanced scientific platforms, data connectivity, software engineering, and emerging technologies. DTP brings science and technology together to strengthen scientific workflows and enable increasingly data- and AI-driven discovery.

Within DTP, Data Foundry brings together complementary capabilities across architecture, scientific methods, scalable engineering, and scientific data preparedness to make scientific data more connected, reusable, and ready for advanced analytics and AI.

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 Architecture4Insight, this leader will partner closely with Methods4Insight and Scale4Insight 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 Architecture4Insight 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 governance policies to make data trusted, interoperable, and reusable.

Preferred Qualifications

Experience in pharmaceutical, biotechnology, life sciences, or research-intensive environments.
Expertise in scientific data management, harmonization, metadata, governance, information architecture, or AI/data readiness.
Demonstrated success building, leading, and developing high-performing technical teams.
Exceptional leadership, communication, and organizational influence skills.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is

$177,000 - $281,600

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.

#WeAreLilly

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Pay

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is $177,000 - $281,600 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.

Location & working pattern