Level

OpenAI

Data Scientist, Real Estate & Workplace

OpenAI is hiring a Data Scientist, Real Estate & Workplace for a remote role open to applicants in United States. It pays $266k-$385k a year and Level rates it ; you can apply on OpenAI.

Level's read on this job

  • Works on AI ●●●○ is how Level rates this data scientist role: the daily work is on AI products, without building the model.
  • The listed pay starts 60% above the typical data scientist posting on Level.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include AI evaluation, AI research and data science.
  • Level lists 793 other open roles at OpenAI.

AI in this role

Lead data science for real estate and workplace operations using advanced analytics and agentic tools.

ai-evaluationai-researchdata-scienceforecastingoptimizationexperimentationanalytics

About the Role

We’re hiring a Data Scientist to support Real Estate & Workplace (REW), a fast-moving global team focused on creating workplaces that help OpenAI’s people do their best work while scaling the company’s real estate and workplace operations. Our work is grounded in understanding how people use space and services, collaborate across physical and digital environments, and experience the workplace.

REW’s scope spans portfolio strategy, design and construction, space planning, sustainability, workplace experience, and global operations. You’ll work comfortably across this broad, sometimes messy data landscape and build trusted relationships across the domain. The work informs high-impact decisions with immediate, visible effects—from where teams work and how space and services are allocated to which investments move forward and how workplace experiences evolve. This is a high-ownership Data Science role spanning analytical strategy and hands-on execution. Working at the forefront of AI-native analytics, you’ll help define the future of workplace operations at OpenAI rather than follow an established playbook. You’ll shape REW’s Data Science roadmap, identify where forecasting, experimentation, and optimization can drive impact, and translate business priorities into an analytical plan. You’ll own the stakeholder-facing execution layer—including owning agent-built dashboards, recurring reporting, models, and decision tools—along with analytical requirements, validation, adoption, and measurable business impact.

In this role, you’ll be partnered closely with Finance, People Analytics, IT, and REW leaders. You’ll own problems end to end—from framing and prioritization through analysis, recommendation, delivery, adoption, and iteration—so the work drives measurable business outcomes.

What You’ll Do

  • Own ambiguous, high-impact problems end to end—from framing and prioritization through delivery, adoption, and iteration.

  • Define success metrics and build measurement, forecasting, experimentation, and optimization frameworks for decisions about people, spaces, and investments.

  • Develop and own agentic dashboards, reporting, models, and decision tools, ensuring they are trusted, governed, and agent-ready.

  • Connect data from workplace sensors, collaboration tools, operations, and financial systems—while identifying and integrating novel data sources—to guide decisions about space, services, employee experience, and investments.

  • Communicate assumptions, trade-offs, and recommendations clearly to technical, operational, and executive stakeholders.

What We’re Looking For

  • Ability to thrive in ambiguity, take ownership, and balance rigor with speed.

  • Familiarity with AI-assisted analytics, collaboration technologies, and operational platforms.

  • Experience in Data Science or Decision Science, ideally in operational, financial, workplace, or internal-tools environments.

  • Strong grounding in applied statistics, causal inference, forecasting, and model evaluation; fluent in SQL and Python.

  • Proven ability to turn messy, broad datasets into high-impact decisions and measurable outcomes.

  • Enthusiasm for pioneering AI-native analytics and working with agentic dashboards and decision systems.

  • Exceptional communication skills across operators, engineers, cross-functional partners, and senior leaders.



Nice to Have

  • Experience building operational automation or decision systems for prioritization, forecasting, or optimization.

  • Experience analyzing human behavioral or organizational-network data from workplace sensors and collaboration technologies such as messaging, meetings, calendars, or workplace platforms.

  • Experience creating analytical, measurement, or governance frameworks in fast-changing environments.

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 OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.

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.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

OpenAI Global Applicant Privacy Policy

At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

How we rate this

Data Scientist, Real Estate & Workplace at OpenAI rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI EvaluationAI ResearchData ScienceForecastingOptimizationExperimentationAnalytics

Also common in data scientist jobs at this level

Pay

This job starts at
$266k
Typical data scientist job
$166k

This posting starts 60% above the typical data scientist job. See data scientist jobs

Questions you could be asked

  1. How do you decide that one model's output is better than another's for a given task?
  2. Tell me about a research question you investigated. What did you find?
  3. Tell me about a project where data science was part of your work. What did you do?
  4. Tell me about a project where forecasting was part of your work. What did you do?
  5. Tell me about a project where optimization was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI Evaluation, AI Research, Data Science, Forecasting, and Optimization. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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