Data Scientist, Real Estate & Workplace

OpenAI; Mountain View (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

OpenAI in Mountain View is seeking a Data Scientist to empower the Real Estate & Workplace (REW) team with analytics that scale space planning, occupancy, and investments. You'll own the analytical roadmap and deliver dashboards and models used by finance, IT, and leadership.

This high-ownership role requires turning messy data into measurable outcomes, building forecasting and optimization frameworks, and communicating results clearly across technical and executive audiences.

Qualifications

• Experience turning messy, broad datasets into actionable decisions and metrics.
• Ability to own projects from framing to delivery and impact.
• Strong communication with technical, operational, and executive stakeholders.
• Experience with forecasting, experimental design, and model evaluation.

Responsibilities

• Own ambiguous, high-impact problems end to end—from prioritization to delivery.
• Define success metrics and build forecasting, experimentation, and optimization frameworks.
• Develop and own dashboards, reporting, models, and decision tools.
• Integrate data from workplace sensors, collaboration tools, and financial systems to guide decisions.
• Communicate assumptions, trade-offs, and recommendations clearly to stakeholders.

Skills

SQL

Python

Data Science

Forecasting

Causal Inference

Model Evaluation

Job description

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.

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

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