Director, Data and AI Product Owner, Research
Gilead Sciences
August 08, 2026
Remote friendly (San Francisco Bay Area)
United States
IT
Director, Data/AI Product Owner, Research
Key Responsibilities:
- Define and lead product strategy and multi-year roadmap for AI-enabled research capabilities.
- Partner with senior Research leaders to identify high-impact AI opportunities, pain points, and advanced analytics opportunities; develop business cases.
- Lead and mentor Product Owners and Product Managers; prioritize backlog by business value, risk, technical feasibility, and alignment with enterprise data/AI strategy.
- Establish and scale product operating model for consistent delivery.
- Translate business objectives into product requirements/backlog items (data architecture, platform constraints, scalability).
- Own end-to-end product vision and multi-year roadmap for AI-enabled research decision support; balance priorities, constraints, and value realization.
- Align solutions with data architecture, AI/ML capabilities, and platforms.
- Define and track success metrics (cost reduction, productivity gains, adoption, satisfaction) and drive continuous improvement.
- Drive change management and user adoption (UX, communications, training, feedback loops).
- Own vendor/partner strategy for product support, including external capacity and AI/LLM capabilities (with IT/Procurement).
- Identify gaps between current and target capabilities; influence Databricks/AWS and data platform evolution.
- Serve as trusted advisor to research leadership; apply business/financial acumen to evaluate trade-offs and recommend solutions.
Key Skills & Experience (Qualifications):
- Bachelor’s with 12+ years or Master’s/PhD with 10+ years in a relevant field.
- Deep understanding of drug discovery and development.
- Experience as Product Owner/Product Manager; translating needs into scalable data/AI solutions.
- Strong stakeholder management and influence.
- Business and financial acumen (ROI, cost-to-value, long-term platform investment).
- Solid understanding of data/AI architecture and ability to discuss trade-offs with engineering/data science.
- Familiarity with modern data platforms (Databricks, AWS).
- Proven Agile/Scrum experience; metrics-driven prioritization/delivery.
Optional Differentiators:
- Experience with AI/ML in drug discovery.
- Exposure to generative AI use cases.
- Familiarity with scientific platforms (ELN, Assay Management, Scientific Research, LIMS, HPC systems).
Application Instructions:
- For Current Gilead Employees and Contractors: apply via the Internal Career Opportunities portal in Workday.
Key Responsibilities:
- Define and lead product strategy and multi-year roadmap for AI-enabled research capabilities.
- Partner with senior Research leaders to identify high-impact AI opportunities, pain points, and advanced analytics opportunities; develop business cases.
- Lead and mentor Product Owners and Product Managers; prioritize backlog by business value, risk, technical feasibility, and alignment with enterprise data/AI strategy.
- Establish and scale product operating model for consistent delivery.
- Translate business objectives into product requirements/backlog items (data architecture, platform constraints, scalability).
- Own end-to-end product vision and multi-year roadmap for AI-enabled research decision support; balance priorities, constraints, and value realization.
- Align solutions with data architecture, AI/ML capabilities, and platforms.
- Define and track success metrics (cost reduction, productivity gains, adoption, satisfaction) and drive continuous improvement.
- Drive change management and user adoption (UX, communications, training, feedback loops).
- Own vendor/partner strategy for product support, including external capacity and AI/LLM capabilities (with IT/Procurement).
- Identify gaps between current and target capabilities; influence Databricks/AWS and data platform evolution.
- Serve as trusted advisor to research leadership; apply business/financial acumen to evaluate trade-offs and recommend solutions.
Key Skills & Experience (Qualifications):
- Bachelor’s with 12+ years or Master’s/PhD with 10+ years in a relevant field.
- Deep understanding of drug discovery and development.
- Experience as Product Owner/Product Manager; translating needs into scalable data/AI solutions.
- Strong stakeholder management and influence.
- Business and financial acumen (ROI, cost-to-value, long-term platform investment).
- Solid understanding of data/AI architecture and ability to discuss trade-offs with engineering/data science.
- Familiarity with modern data platforms (Databricks, AWS).
- Proven Agile/Scrum experience; metrics-driven prioritization/delivery.
Optional Differentiators:
- Experience with AI/ML in drug discovery.
- Exposure to generative AI use cases.
- Familiarity with scientific platforms (ELN, Assay Management, Scientific Research, LIMS, HPC systems).
Application Instructions:
- For Current Gilead Employees and Contractors: apply via the Internal Career Opportunities portal in Workday.