Data Scientist, Real Estate & Workplace

About the RoleWe’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 DoOwn 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 ForAbility 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 HaveExperience 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 OpenAIOpenAI 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 PolicyAt 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.Compensation Range: $230K - $342KLocationSan Francisco; Mountain ViewEmployment TypeFull timeLocation TypeHybridDepartmentData ScienceCompensation$230K – $342K • Offers EquityThe base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings AccountsPre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)401(k) retirement plan with employer matchPaid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)Mental health and wellness supportEmployer-paid basic life and disability coverageAnnual learning and development stipend to fuel your professional growthDaily meals in our offices, and meal delivery credits as eligibleRelocation support for eligible employeesAdditional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.More details about our benefits are available to candidates during the hiring process.This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.