Data Scientist, Codex

Codex is OpenAI’s first-party developer product focused on agentic software engineering. We’re building tools that help engineers design, write, test, and ship code faster—safely and at scale. We partner tightly with research and product to translate model advances into tangible developer productivity.

About the Role

As a Data Scientist on Codex, you will measure and accelerate product-market fit for AI developer tools. You’ll define what “developer productivity” means for our product, run experiments on new coding models and UX, and pinpoint where the model helps or hurts across languages and tasks. Your insights will directly shape how an entire industry builds software.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will

• Embed with the Codex product team to discover opportunities that improve developer outcomes and growth
• Design and interpret A / B tests and staged rollouts of new coding models and product features
• Define and operationalize metrics such as suggestion acceptance, edit distance, compile / test pass rates, task completion, latency, and session productivity
• Build dashboards and analyses that help the team self-serve answers to product questions (by language, framework, repo size, task type)
• Diagnose failure modes and partner with Research on targeted improvements (model quality signals, user feedback, evals)

You might thrive in this role if you have

You could be an especially great fit if you have

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

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