Director, Data and AI Product Owner, Research
Gilead Sciences
August 30, 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, incorporating data architecture, platform constraints, and scalability.
- Own end-to-end product vision and multi-year roadmap for Research decision-support capabilities.
- Align solutions with data architecture, AI/ML capabilities, and platforms.
- Define and track success metrics (cost reduction, productivity gains, user adoption, satisfaction) and drive continuous improvement.
- Drive change management and user adoption (UX design, communications, training, feedback loops).
- Own vendor/partner strategy for product support, including external capacity and AI/LLM capabilities (with IT and Procurement).
- Identify capability gaps and influence Databricks/AWS/data platform evolution with technical leaders.
- Serve as a trusted advisor to research leadership using business/financial acumen.
Key Skills & Experience
- Bachelor’s with 12+ years or Master’s/PhD with 10+ years in relevant field.
- Deep understanding of drug discovery and development.
- Product Owner/Product Manager experience; strong record translating business needs into scalable data/AI solutions.
- Stakeholder management/influence; trusted advisor to senior research leaders.
- Business and financial acumen (ROI, cost-to-value, long-term platform investments).
- Solid data/AI architecture knowledge; ability to discuss trade-offs with engineering/data science.
- Familiarity with Databricks and AWS.
- Agile/Scrum experience; metrics-driven prioritization and delivery.
Optional Differentiators
- AI/ML in drug discovery; generative AI exposure; familiarity with ELN, assay management, scientific research, LIMS, HPC.
Application Instructions
- Apply via the Internal Career Opportunities portal in Workday (for current Gilead employees/contractors).
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, incorporating data architecture, platform constraints, and scalability.
- Own end-to-end product vision and multi-year roadmap for Research decision-support capabilities.
- Align solutions with data architecture, AI/ML capabilities, and platforms.
- Define and track success metrics (cost reduction, productivity gains, user adoption, satisfaction) and drive continuous improvement.
- Drive change management and user adoption (UX design, communications, training, feedback loops).
- Own vendor/partner strategy for product support, including external capacity and AI/LLM capabilities (with IT and Procurement).
- Identify capability gaps and influence Databricks/AWS/data platform evolution with technical leaders.
- Serve as a trusted advisor to research leadership using business/financial acumen.
Key Skills & Experience
- Bachelor’s with 12+ years or Master’s/PhD with 10+ years in relevant field.
- Deep understanding of drug discovery and development.
- Product Owner/Product Manager experience; strong record translating business needs into scalable data/AI solutions.
- Stakeholder management/influence; trusted advisor to senior research leaders.
- Business and financial acumen (ROI, cost-to-value, long-term platform investments).
- Solid data/AI architecture knowledge; ability to discuss trade-offs with engineering/data science.
- Familiarity with Databricks and AWS.
- Agile/Scrum experience; metrics-driven prioritization and delivery.
Optional Differentiators
- AI/ML in drug discovery; generative AI exposure; familiarity with ELN, assay management, scientific research, LIMS, HPC.
Application Instructions
- Apply via the Internal Career Opportunities portal in Workday (for current Gilead employees/contractors).