Data Program Manager, Science

About the Role

As a Data Program Manager, Science, you will help researchers develop and execute scientific data programs, connecting OpenAI’s research priorities with relevant data, expertise and external partners.

You’ll work closely with researchers to understand their needs, assess the scientific and practical value of opportunities, and develop partnerships across the scientific ecosystem. The work could range from acquiring existing datasets to shaping research collaborations. You’ll carry opportunities from initial investigation through commercial discussions, agreements, delivery and research use, exercising sound judgement around sensitive data and relationships.

Our current work focuses particularly on biology and chemistry. We welcome different combinations of scientific, technical and partnership experience.

This role is based in our San Francisco HQ.

In this role, you will

• Develop data strategies with Research. Translate research goals, model limitations and evaluation gaps into evidence needs and success criteria. Compare acquisition with internal, public and commissioned alternatives.
• Find distinctive sources for research. Build trusted local and international relationships across research and industry, including organisations at the scientific frontier.
• Assess opportunities in scientific context. Inspect samples for provenance, context, quality and completeness. Assess usefulness, involving researchers and specialists as needed.
• Shape partnerships with lasting scientific value. Understand partners’ ambitions and define pilots, deliverables and acceptance criteria, considering expertise, scientific contribution and continuing relationships alongside commercial terms.
• Lead commercial and operational execution. Develop proposals, assess pricing and negotiate terms. Coordinate Legal, Privacy, Security, Procurement and engineering to clarify permissions, responsibilities and delivery.
• Navigate sensitive collaborations. Understand institutional interests and confidentiality. Identify ethical, privacy, security and misuse concerns early, involving specialists to develop responsible arrangements.
• Follow through into research use. Coordinate preparation, ingestion, access and documentation. Gather researcher feedback to inform whether to expand, change or stop.
• Make thoughtful portfolio decisions. Recommend options based on research value, cost, timing and capacity. Identify shared needs and opportunities for useful collaboration across projects.
• Make the work more repeatable. Use code, APIs, automation and AI tools to improve sourcing, assessment and delivery. Resolve recurring blockers with engineers and retain partner knowledge and research feedback.

You might thrive in this role if you

• Have substantial grounding in biology, chemistry or related sciences through research, industry or equivalent experience, and engage critically with methods and evidence.
• Have delivered complex scientific, data or partnership projects, with depth in one or more of scientific data and evaluation, commercial partnerships or research collaborations across organisations.
• Exercise sound judgement: test claims, match evidence to research needs and make clear recommendations while acknowledging uncertainty.
• Work directly with data: inspect unfamiliar files, investigate quality and use Python, SQL, APIs and AI-assisted coding to answer questions and reduce manual work.
• Build trust through careful listening, precise questions and thoughtful negotiation. You bring relevant local and international relationships, or a demonstrated ability to develop them, and understand what partners value beyond the transaction.
• Exercise discretion, recognising the limits of your expertise and authority and when scientific, ethical or safety questions need specialist input.
• Thrive in a fast-moving environment, taking broad ownership across multiple projects and moving readily between scientific, technical and commercial questions. You prioritise thoughtfully as needs change, making clear decisions about where to focus and what can wait.
• Enjoy getting your hands dirty, bringing energy and creative problem solving to unfamiliar or ambiguous opportunities. You turn them into practical plans and follow through on the details.
• Learn exceptionally quickly, developing your understanding of AI training, evaluation and unfamiliar research areas to become a useful collaborator.
• We welcome different combinations of scientific, technical and partnership experience. You do not need equal depth in every area.