OpenAI Data Scientist Interview Guide

OpenAI DS interviews focus heavily on your ability to understand and work with hypothetical experiments, and you’ll be asked to show off your skills and experience by tackling real-world problems around AI model adoption, usage, and infrastructure.

In addition to your skills with SQL and Python, they’ll test your ability to work around constraints, particularly time and infrastructure constraints. OpenAI’s teams move quickly, and they want to make sure you’re able to keep up.

They’ll also task you with debugging and deploying AI-generated code, which can be tricky, as AI tools make different choices and different mistakes than those made by human developers.

Interview Process

OpenAI's interview process is extremely varied between teams, so it's near impossible to say how the "standard process looks." However, here’s a look at the closest approximation for what a process might look like:

1. Recruiter screen: A brief call to review your past experience and determine whether there is a skills match.
2. Technical screen: A two-part assessment, starting with a take-home assignment and then a 1-hour in-person review.
3. A final round of five interviews, virtual or onsite in San Francisco, consisting of: hiring manager interview, 2 data science case studies, data science Q&A, and project management case study.

Recruiter screen

This brief call will focus on your data science experience, particularly in the enterprise space. The recruiter will also ask about your experience with AI, in particular, working with the output of AI coding tools.

If time allows, they will also ask about your interest in OpenAI and familiarity with their projects.

Recruiter Screen Questions:

Technical screen

This two-part assessment starts with a take-home data challenge that you will have 48 hours to complete. Once it’s complete, the interviewers will review and, if you pass, call you in to present your work.

This challenge will be based on a real-world business problem, such as a feature launch or user behavior analysis. It will also involve you understanding and debugging AI-generated code.

Once you complete the challenge, you can send it in using whatever format you prefer, as long as it allows them to understand your proposed solution.

The review lasts 30 minutes, and you’ll discuss your approach and answer the reviewer’s questions. The next half hour will focus on a more generic SQL data manipulation task.

Technical Screen Questions:

Final round

For these interviews, you can choose to interview in person at their San Francisco office or virtually. The interviews may all be scheduled for a single day or spread over two days:

Hiring manager interview

The hiring manager will ask you to analyze and discuss your experience on a project you recently worked on. You’ll be asked about the project's technical and collaborative aspects.

As you describe your approach, they will ask you to define the tools you used and explain why you chose certain methods over others.

They will also want to know about any particular challenges you faced, for example, an unrealistic project timeline or an A/B test that produced inconclusive results. They will want to know how you approached these issues and what solutions you developed.

Additionally, they will ask about how you work with others, particularly project managers and the product team. Did you have to defend your conclusions, and if so, how did you do it?

The manager will include more general questions about your interest in AI and in OpenAI in particular. Even if you don’t have any AI experience, they’ll want to know that you are familiar with their products and their mission.

Hiring Manager Questions:

Data science case study

You’ll speak with a data scientist who may also be joined by a shadow, and your conversation will center around a case study.

You’ll be given metrics on a feature and asked to analyze them, make strategic suggestions, and decide whether to launch it.

The question is meant to test your knowledge of statistics, finding the P-value, creating a multifactorial experiment to test a hypothesis, and other practical methods.

Data Science Case Study Questions:

Data science Q&A

Like the prior interview, this interview will be with a data scientist and, potentially, a shadow. They will ask you questions about complex statistical principles.

In addition, they will ask you to apply these principles and methods to real-world problems and describe how they can assist you with solving them.

The concepts in this round are fairly academic and may be challenging for someone without an advanced degree in statistics or extensive relevant experience.

Data Science Q&A Questions:

Project management case study

This is another case study, but the interview will be conducted by a project manager and will focus more on your collaborative skills and project strategy.

You’ll be given a case, such as a shift in user behavior, and the PM will ask you to lay out your step-by-step approach.

They may also add constraints, such as time and resource limitations. OpenAI embraces moving quickly and decisively, so being able to handle constraints is important.

There will also be some discussion about your collaborative skills and how you work with others, particularly how you explain your methods and handle conflict.

Project Management Case Study Questions:

Senior data scientist case study

This final case study will be conducted by a senior DS on the team, and may also include a shadow. The interview will mainly focus on your use of DS techniques.

Given a specific case, such as a product launch, the senior DS will want to know which techniques you will favor and how you will handle potential issues, such as a lack of high-quality data or a small sample size.

As with the other rounds, being able to alter your approach to meet resource and time constraints is important, as this is a necessary skill for day-to-day work at OpenAI.

Senior DS Case Study Questions:

Common Mistakes

Here are some common mistakes data scientist candidates make when interviewing for a position at OpenAI:

• A lack of familiarity with OpenAI’s suite of products and goals, as the use cases you see will relate directly to them
• Unfamiliarity with AI-generated code, as this is a key component of OpenAI’s interview process
• Not preparing to discuss relevant statistical principles and methods, especially more advanced, “PhD-level” techniques
• Showing an unwillingness to work around infrastructural obstacles, overly reliant on process
• Struggling to work with or around constraints, such as time and infrastructural limitations, or a lack of directly usable data
• Limited ability to work across teams and collaborate with people outside of the DS discipline

Interview Prep

Learn as much as you can about OpenAI’s goals: Because their interviews are so centered around use cases, it’s important that you understand the philosophy and approach that OpenAI has taken to their products.

Work with AI tools: Familiarity with SQL and Python is a given, but it’s also important that you be able to read and understand the output of LLM-powered coding assistants. Because these tools do not operate the same way as human coders, their choices and mistakes are different, so you’ll need to know what to look for when working with AI-generated code.

Prepare for constraints: One of the chief issues in the AI space is the issue of capacity, extracting computational resources in the most efficient way, working with limited resources, and so on. Preparing to work quickly with fewer resources than you’d like is critical for passing these rounds.

About the Role

What will you do as a data scientist at OpenAI?

• Build tools to measure performance: Whether you’re measuring the adoption rates of a new feature or testing multivariate pricing strategies, you’ll use your skills to measurably improve the financial performance of OpenAI’s tools.
• Automating reporting and data analyses: You’ll help build and iterate on automated data gathering and analysis tools, granting your whole team access to actionable data-derived insights.
• Conduct cross-functional data science projects: You’ll provide expert insight and guidance, leading cross-functional data science and research initiatives.

Core Responsibilities

Data scientists and OpenAI typically work on a particular product, team, or vertical, such as financial data, agentic AI, marketing, product development, or infrastructure. Here are some of the general responsibilities they have to meet:

• Build dashboards and automated tools that allow team members to draw powerful data-backed insights.
• Conduct experiments and tests to inform decisions on products, pricing, efficiency, and growth.
• Define key metrics for the success of different features and changes.
• Work with other team members to help them understand the results of your experiments and come up with new approaches

Compensation

As the largest and most well-funded AI model company, OpenAI pays its data scientists well above the tech industry average. Levels.fyi indicates that OpenAI DSs make the following in total compensation:

L4: $464,000/yr

L5: $820,000/yr

Job Requirements

Experience

OpenAI hires data scientists with 5-7 years of relevant experience, proficiency in SQL, Python, and Tableau, and experience working cross-functionally and delivering projects from start to finish.

Education

DS roles require a master’s degree or PhD in a quantitative field, but OpenAI may accept less with significant relevant career experience.

Resources

• OpenAI Careers Page
• OpenAI Interview Guide
• OpenAI Charter
• Data Science Interview Prep
• Generative AI Interview Prep
• OpenAI Interview Questions
• Data Analysis Interview Questions

FAQs

Do I need to have AI experience to work as a data scientist at OpenAI?

They do not list AI experience as a requirement, but you will need experience working with AI coding assistants and thorough knowledge of OpenAI’s tools and products.

How long is the OpenAI Data Scientist interview process?

Although the exact length will vary, their guide says that the process should take between 2-3 weeks from the application to decision.

Does OpenAI offer internships?

OpenAI’s Emerging Talent program offers early career opportunities and internships, which are posted on their Careers site when available.

They also offer a six-month AI Residency for researchers and experts without direct AI experience.

If I am rejected, how long should I wait before reapplying to OpenAI?

OpenAI asks rejected candidates to wait 1 year before reapplying. And sometimes they make exceptions on this depending on interview performance.

Does OpenAI assign its Data Scientists to teams, or do you apply directly to a team?

Depending on how you were recruited, your experience, and your level, you may apply directly to a team via their Careers page or be routed to one that aligns with your level and past work experience.