Data Scientist, GTM

Details

OpenAI’s GTM Data Science team helps shape how its products are adopted, monetized, and scaled across organizations. The team works at the intersection of Product, Go-to-Market, Finance, Research, and Data, turning product usage, customer evidence, and market signals into decisions that grow durable enterprise value.

This role owns the analytical strategy for enterprise knowledge-worker adoption across ChatGPT Work, Codex, and connected enterprise systems. The focus is on understanding how products become embedded in everyday work through activation, retained usage, workflow depth, and realized value.

Responsibilities

• Define a trusted measurement framework for knowledge-worker adoption, including identity, eligible populations, activation, retained usage, penetration, workflow depth, feature adoption, and monetization.
• Map the knowledge-worker journey from initial exposure through first successful task, repeated workflows, multi-surface usage, and durable adoption.
• Identify which personas, functions, use cases, product capabilities, and account conditions are associated with deep and retained usage.
• Design and evaluate experiments and quasi-experiments across onboarding, enablement, workflow templates, connectors, pilots, customer deployment support, and product launches.
• Combine behavioral data with customer and field evidence, translating findings into recommendations for Product, GTM, Finance, and executive audiences.
• Operationalize successful work through durable datasets, scorecards, recurring business narratives, and decision cadences.
• Partner with Analytics Engineering and product teams to improve instrumentation and data quality.
• Work through imperfect telemetry, overlapping product surfaces, evolving definitions, and ambiguous business questions.
• Partner with GTM, Product, Finance, Research, Customer Deployment, Analytics Engineering, and Data Science.

Requirements

• Significant experience in data science, product analytics, growth analytics, economics, statistics, or a related quantitative field.
• Strong hands-on ability in SQL and Python, including experience working with large and imperfect behavioral datasets.
• Experience defining activation, retention, engagement, funnel, or product-adoption metrics.
• Strong knowledge of experimentation, causal inference, cohort analysis, and segmentation.
• Ability to translate ambiguous business questions into structured analyses, independently define analytical direction, and frame tradeoffs for senior stakeholders.
• Strong written and verbal communication skills, including the ability to influence senior technical and non-technical stakeholders.
• Ability to create clarity from problems without stable definitions, clean datasets, or a settled playbook.
• Ability to think in terms of user journeys and behavioral mechanisms rather than only dashboards and aggregate metrics.
• Ability to distinguish product usage from durable customer value and simulated value from realized business outcomes.
• Proactive stakeholder alignment, decision documentation, and identification of data-quality risks.

Preferred Qualifications

• Experience with enterprise SaaS, collaboration products, AI products, developer tools, productivity software, or multi-product platforms.
• Experience connecting product usage to revenue, expansion, customer health, enablement, or other GTM interventions.
• Experience with identity resolution, cross-surface journeys, telemetry design, evolving product taxonomies, or qualitative customer evidence.
• Experience helping establish a new data science area, operating model, technical roadmap, or recurring executive decision cadence.

Benefits

• Base salary of $290,000–$340,000 per year, plus equity.
• Performance-related bonuses for eligible employees.
• Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
• Pre-tax accounts for health, dependent care, and commuter expenses.
• 401(k) retirement plan with employer match.
• Paid parental, medical, and caregiver leave.
• Paid time off, company holidays, office closures, and paid sick or safe time as required by law.
• 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 may include charitable donation matching and wellness stipends.

OpenAI is an equal opportunity employer and is committed to providing reasonable accommodations to applicants with disabilities. Background checks for applicants will be administered in accordance with applicable law.