Data Program Manager, Science

The posting, as OpenAI wrote it

About the Team
OpenAI’s Research Data team exists to accelerate the evaluation, safety and capabilities of our models and products. Made up of technical operators and software engineers, we design the methods through which we acquire and create data.

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 fee

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