Data Scientist, Codex

About the Team

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

• 5+ years in a quantitative role at a developer-facing or high-growth product

• Fluency in SQL and Python; comfort with experiment design and causal inference

• Experience defining product metrics tied to user value

• Ability to communicate clearly with PM, Eng, and Design—and to influence product direction
  

You could be an especially great fit if you have

• Strong programming background; ability to prototype, run simulations, and reason about code quality

• Familiarity with IDE/extension telemetry or developer tooling analytics

• Prior experience with NLP/LLMs, code models, or evaluations for generative coding

About OpenAI

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. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 

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.

For additional information, please see .

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

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