Data Scientist, Analytics Enablement

OpenAI • San Francisco, CA

1d • $347,000 - $385,000

About The Position

The Strategic Finance Data Science team helps OpenAI understand business performance and make informed decisions about growth, revenue, and resource allocation. The team partners with Strategic Finance, Data Engineering, and business teams to build trusted metrics, explain changes, and support forecasting, planning, pricing, and investment decisions.

The Data Scientist, Analytics Enablement turns complex financial and business questions into reliable data products, clear analyses, and actionable recommendations. This hands-on individual contributor role spans the analytical workflow: defining questions, establishing trustworthy metrics and datasets, investigating drivers, and helping partners act on findings. It combines technical depth in analytics engineering with analytical judgment and close partnership with Strategic Finance. The work supports executive reviews and day-to-day business decisions.

Requirements

• Strong SQL and analytical data-modeling skills.
• Experience turning large, complex datasets into reliable analyses and reusable data products.
• Ability to reason carefully about metrics, cohorts, denominators, measurement changes, and uncertainty, and investigate whether an unexpected result reflects the business or the data.
• Experience building dashboards or recurring reporting used by business partners, and ability to explain the decisions they enabled.
• Sound business judgment and ability to independently scope an ambiguous problem, prioritize work, and deliver an end-to-end solution.
• Clear communication of technical findings and ability to work effectively with Finance, data scientists, engineers, and other business partners.
• Ability to use Python or a comparable analytical tool to investigate data and automate repetitive work.

Responsibilities

• Define and maintain trusted metrics and analytical datasets for revenue, usage, customer performance, compute consumption, and margin, with clear definitions and appropriate product, customer, and cohort detail.
• Build automated dashboards and recurring reporting to help Finance leaders and operating teams understand performance, spot changes, and prioritize investigation.
• Explain movements in business results and variances against expectations by examining underlying drivers, validating data quality, and distinguishing evidence from assumptions.
• Translate ambiguous questions about growth, retention, monetization, pricing, and resource efficiency into structured analyses and practical recommendations.
• Partner with forecasting specialists and Finance to provide reliable inputs, driver analyses, and scenario assumptions for forecasts and long-range plans.
• Work with Data Engineering to improve the quality and usability of underlying data, and develop reusable analytical models and workflows that reduce manual effort.
• Communicate findings clearly, align stakeholders on trade-offs, and follow through to understand whether the analysis or data product improved the decision.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed