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OpenAI's Research Data team is seeking a Data Program Manager, Science to accelerate the evaluation, safety and capabilities of AI models and products. You will help researchers develop and execute scientific data programs, connecting OpenAI's research priorities with relevant data, expertise and external partners.
In this role, you will develop data strategies with researchers by translating research goals, model limitations and evaluation gaps into evidence needs and success criteria. You'll find distinctive sources for research by building trusted relationships across the scientific ecosystem, including organizations at the research frontier. You'll assess opportunities in scientific context by inspecting samples for provenance, quality and completeness, and involving researchers and specialists as needed.
You will shape partnerships with lasting scientific value by understanding partners' ambitions and defining pilots, deliverables and acceptance criteria. You'll lead commercial and operational execution by developing proposals, assessing pricing and negotiating terms while coordinating with Legal, Privacy, Security, Procurement and engineering teams. You'll navigate sensitive collaborations by understanding institutional interests, confidentiality requirements, and identifying ethical, privacy, security and misuse concerns early.
You'll follow through into research use by coordinating preparation, ingestion, access and documentation, and gathering researcher feedback. You'll make thoughtful portfolio decisions by recommending options based on research value, cost, timing and capacity. You'll also make the work more repeatable by using code, APIs, automation and AI tools to improve sourcing, assessment and delivery.
The team's current work focuses particularly on biology and chemistry. This role is based in OpenAI's San Francisco headquarters.
QUALIFICATIONS & REQUIREMENTS:
- Substantial grounding in biology, chemistry or related sciences through research, industry or equivalent experience, with critical engagement with methods and evidence
- Demonstrated delivery of complex scientific, data or partnership projects, with depth in one or more of: scientific data and evaluation, commercial partnerships, or research collaborations across organizations
- Sound judgment: ability to test claims, match evidence to research needs and make clear recommendations while acknowledging uncertainty
- Hands-on data work: ability to inspect unfamiliar files, investigate quality and use Python, SQL, APIs and AI-assisted coding to answer questions and reduce manual work
- Ability to build trust through careful listening, precise questions and thoughtful negotiation; relevant local and international relationships or demonstrated ability to develop them
- Discretion and recognition of limits of expertise and authority; knowing when scientific, ethical or safety questions need specialist input
- Ability to thrive in fast-moving environment, taking broad ownership across multiple projects and moving between scientific, technical and commercial questions
- Problem-solving orientation: energy and creative problem solving for unfamiliar or ambiguous opportunities, turning them into practical plans and following through on details
- Exceptional learning ability: capacity to develop understanding of AI training, evaluation and unfamiliar research areas to become a useful collaborator
- Note: Different combinations of scientific, technical and partnership experience are welcome; equal depth in every area is not required
