Data Program Manager, Science

Details

OpenAI’s Research Data team accelerates the evaluation, safety, and capabilities of its models and products by designing methods to acquire and create data. This role supports researchers in developing and executing scientific data programs, connecting research priorities with relevant data, expertise, and external partners. Current work focuses particularly on biology and chemistry.

Responsibilities

• Develop data strategies with Research by translating research goals, model limitations, and evaluation gaps into evidence needs and success criteria.
• Compare external acquisition with internal, public, and commissioned alternatives.
• Find distinctive research data sources and build local and international relationships across research and industry.
• Assess samples for provenance, context, quality, completeness, and usefulness.
• Shape partnerships by defining pilots, deliverables, and acceptance criteria while considering scientific contribution and ongoing relationships.
• Lead commercial and operational execution, including proposal development, pricing assessment, negotiations, and coordination with Legal, Privacy, Security, Procurement, and engineering.
• Navigate sensitive collaborations, including ethical, privacy, security, confidentiality, and misuse concerns.
• Coordinate data preparation, ingestion, access, and documentation for research use.
• Gather researcher feedback to determine whether initiatives should be expanded, changed, or stopped.
• Make portfolio recommendations based on research value, cost, timing, and capacity.
• 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.

Requirements

• Substantial grounding in biology, chemistry, or related sciences through research, industry, or equivalent experience.
• Experience delivering complex scientific, data, or partnership projects, with depth in one or more of scientific data and evaluation, commercial partnerships, or cross-organizational research collaborations.
• Ability to test claims, match evidence to research needs, make clear recommendations, and acknowledge uncertainty.
• Experience working directly with data, including inspecting unfamiliar files and investigating data quality.
• Experience using 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 a demonstrated ability to develop them.
• Discretion and sound judgment regarding scientific, ethical, safety, privacy, and security questions.
• Ability to take ownership across multiple projects and move between scientific, technical, and commercial questions in a fast-moving environment.
• Creative problem-solving skills and the ability to turn ambiguous opportunities into practical plans.
• Ability to learn quickly about AI training, evaluation, and unfamiliar research areas.
• Different combinations of scientific, technical, and partnership experience are welcome; equal depth in every area is not required.

Benefits

• Equity, performance-related bonuses for eligible employees, and medical, dental, and vision insurance.
• Health Savings Accounts, flexible spending accounts, commuter benefits, and a 401(k) retirement plan with employer match.
• Paid parental, medical, caregiver, and sick or safe leave.
• Paid time off, company holidays, and paid office closures.
• Mental health and wellness support.
• Employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily office meals and eligible meal delivery credits.
• Relocation support for eligible employees.
• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may be provided.