Senior Product Manager, Data and AI Asset Governance Products

GSK•Upper Providence, PA

1d•Hybrid

About The Position

The Onyx Research Data Platform organization represents a major investment by GSK R&D and Digital & Tech, designed to deliver a step-change in our ability to leverage data, knowledge, and prediction to find new medicines. We are a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward: Building a next-generation data and AI experience for GSK’s scientists, engineers, and decision-makers, increasing productivity and reducing time spent on “data mechanics” Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent Aggressively engineering our data at scale to unlock the value of our combined data assets and predictions in real-time Onyx Product Management is at the heart of our mission, ensuring that everything from our infrastructure, to platforms, to end-user facing data assets and environments is designed to maximize our impact on R&D. The Product Management team partners with R&D stakeholders and Onyx leadership to develop a strategic roadmap for all customer-facing aspects of Onyx, including data assets, ontology, Knowledge Graph / semantic search, data / computing / analysis platforms, computational data governance and data intense AI applications. We are seeking an experienced Senior Product Manager to lead the strategy and delivery of Data Governance platform products –the core platform that enables secure, compliant, and scalable management of research data and AI assets across R&D. This platform provides unified capabilities for metadata management, policy enforcement, access control, data classification, and AI asset governance, enabling teams to confidently discover, access, and govern data and AI solutions. You will define and enable the end-to-end user journey across data and AI asset governance, ensuring seamless integration with data platforms, AI/ML systems, and enterprise infrastructure. By partnering closely with engineering and enterprise governance teams, you will align with regulatory standards while accelerating innovation. Ultimately, this platform empowers R&D teams to scale trusted data and AI usage and deliver new medicines for patients.

Requirements

PhD with 2+ years, Master’s with 4+ years, or Bachelor’s with 6+ years of relevant experience.
2+ years of experience in product management with a proven track record of delivering scalable platform capabilities in data governance, data platforms, or AI/ML-enabled systems within enterprise environments.
Experience defining product strategy for data governance platforms, including familiarity with metadata management, data classification, policy enforcement, access control, and data/AI asset lifecycle management.
Knowledge of cloud-native architectures (e.g., AWS, Azure, GCP), API- driven platforms, and scalable data infrastructure required to securely manage and govern data and AI assets in enterprise settings.
Experience working closely with data engineering, platform engineering, security, and compliance teams to build reliable, governed, and reusable data and AI governance capabilities.
Experience driving platform adoption and governance at scale, including defining standards, guardrails, onboarding frameworks, and enablement materials for cross-functional teams.

Nice To Haves

Direct product management experience designing and launching data governance or AI governance platform capabilities, including policy-driven access, metadata frameworks, data/AI asset classification, and end-to-end lifecycle governance across enterprise or scientific workflows.
Hands-on software engineering, data engineering, or data science experience prior to product management, with exposure to data platforms, metadata systems, or AI/ML governance frameworks.
Deep familiarity with modern data governance concepts and technologies, including data catalogs, lineage, data quality, privacy-preserving techniques, and emerging AI governance practices (e.g., model risk management, auditability, explainability).
Experience delivering platform capabilities that manage, index, and govern complex, unstructured scientific or biomedical data, enabling discoverability, access control, and compliant reuse at scale.
Strong understanding of regulatory and compliance requirements in life sciences (e.g., data privacy, sensitive data handling such as IHD), and their implications on data and AI governance design.
Experience designing governance frameworks that extend to AI assets, including model lifecycle governance, dataset provenance, evaluation tracking, and responsible AI guardrails.
Proven ability to define and implement governance standards, policies, and operating models that scale across enterprise data, AI, and application ecosystems.
Hands-on experience with product management and collaboration tools such as Confluence, Jira, Miro, Monday, and Git-based documentation.
Previous experience in life sciences or biopharma R&D is a strong plus.

Responsibilities

Ownership & Strategy Own and drive the vision, roadmap, development, and adoption of Data Governance platform capabilities, ensuring a unified, governed, and high-quality experience across metadata management, policy enforcement, access control, data classification, and AI asset governance.
Define the strategic direction for data and AI governance capabilities, enabling scalable, compliant, and production-ready data and AI usage across R&D.
Customer & Stakeholder Engagement Conduct ongoing customer discovery with data owner/stewards, scientists and AI/ML practitioners to identify emerging needs and translate them into actionable product requirements.
Lead technical product discussions with engineering and scientific leaders to clarify objectives and shape platform direction.
Product Planning & Delivery Collaborate with stakeholders to define governance features, requirements, and success criteria aligned with scientific use cases and business goals.
Drive agile product execution with engineering and program teams, owning prioritization, backlog management, and delivery of high-quality governance capabilities.
Platform Integration & Governance Ensure seamless integration with Data Platform and AI Platform to enable consistent metadata standards, policy-driven access, and lifecycle governance for both data and AI assets.
Coordinate and align roadmap with enterprise and R&D platforms to ensure interoperability, compliance alignment, and a unified governance framework across data, AI, and applications.
Launch, Adoption & Optimization Lead platform launches and change management to ensure clear communication, training, and adoption of governance capabilities across R&D.
Monitor platform usage, policy effectiveness, and compliance metrics; analyze feedback and telemetry to drive continuous improvements in usability, trust, and governance coverage.

Benefits

You will join a team where your work will support real scientific progress.
You will gain exposure to complex technical challenges and build skills that broaden your career.
We welcome candidates from all backgrounds and encourage you to apply if you are ready to contribute, learn, and grow.
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.

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