Senior Director, AI-Ready Scientific Data & Harmonization

BioSpace; San Francisco (CA); On-site; USD 177,000 - 282,000; Full time

Job summary

Lilly seeks a Senior Director, Scientific Data Preparedness to strengthen the foundations for reusable scientific data across workflows. You will set strategies for data harmonization, metadata standards, information flow modeling, and AI readiness, collaborating with Architecture4Insight and enterprise data teams.

The role blends leadership with hands-on technical work, guiding teams and advising stakeholders to ensure data is prepared for computational and AI-enabled discovery.

Qualifications

• BS or higher 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.

Responsibilities

• Build and lead the team responsible for Scientific Data Preparedness.
• Define capability roadmaps, investment priorities, and operating mechanisms.
• 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.
• Provide hands-on leadership for strategic Scientific Data Preparedness initiatives.

Skills

Leadership

Data governance

AI readiness

Metadata standards

Scientific data management

Education

PhD + 6+ years

MS + 8+ years

BS + 10+ years

Job description

Lilly seeks a Senior Director, Scientific Data Preparedness to strengthen the foundations for reusable scientific data across workflows. You will set strategies for data harmonization, metadata standards, information flow modeling, and AI readiness, collaborating with Architecture4Insight and enterprise data teams.

The role blends leadership with hands-on technical work, guiding teams and advising stakeholders to ensure data is prepared for computational and AI-enabled discovery.