Senior Scientific Product Leader, Lab Data & AI

F. Hoffmann-La Roche AG; South San Francisco (CA); On-site; USD 126,000 - 234,000; Full time

Benefits offered by this job

Discretionary annual bonus

Onsite at South San Francisco campus

Job summary

Genentech is seeking a Senior Product Leader for Lab Workflows & Data to define strategy and a multi-year roadmap connecting study design, data lifecycle, and AI-enabled insights. You will lead cross-functional teams across research, data/AI, and engineering, delivering governed, reusable datasets for scientific discovery.

The role emphasizes end-to-end product ownership, with a focus on onboarding, adoption, and measurable outcomes that reduce cycle time and improve data quality.

Qualifications

• 5+ years of product leadership in life-sciences R&D, including end-to-end ownership of a complex product area serving scientists and lab operations.
• Demonstrated AI product leadership in scientific research and ability to connect AI/ML priorities to scientific outcomes.
• Strong systems and data-governance acumen; experience with API-first, event-driven integration and data stewardship.

Responsibilities

• Define the vision, strategy, and multi-year roadmap for lab workflows, research data, and AI-enabled capabilities.
• Lead discovery with PIs, lab scientists, assay owners, and operations to translate needs into prioritized product requirements and success criteria.
• Drive governance, provenance, metadata, and interoperability across ELN/LIMS, lab automation, and data platforms to enable reproducible research.

Skills

Product leadership

AI product leadership

Data governance

Stakeholder leadership

Education

Advanced life-science degree

Tools

ELN/LIMS integration

Job description

Genentech is seeking a Senior Product Leader for Lab Workflows & Data to define strategy and a multi-year roadmap connecting study design, data lifecycle, and AI-enabled insights. You will lead cross-functional teams across research, data/AI, and engineering, delivering governed, reusable datasets for scientific discovery.

The role emphasizes end-to-end product ownership, with a focus on onboarding, adoption, and measurable outcomes that reduce cycle time and improve data quality.