Data Scientist, Real Estate & Workplace
Remote • San Francisco • FullTime
Posted 25d ago
About the job
We’re hiring a Data Scientist to support our fast-moving global Real Estate & Workplace (REW) team, focused on creating workplaces that enable OpenAI’s people to do their best work while scaling operations. This role is grounded in understanding how people use space and services, collaborate across environments, and experience the workplace. You’ll work across a broad data landscape, build trusted relationships, and inform high-impact decisions with immediate, visible effects. This is a high-ownership role spanning analytical strategy and hands-on execution, where you’ll help define the future of workplace operations at OpenAI using AI-native analytics. You’ll shape the Data Science roadmap, identify opportunities for forecasting, experimentation, and optimization, and translate business priorities into an analytical plan. You will own stakeholder-facing execution, including agent-built dashboards, recurring reporting, models, and decision tools, ensuring their adoption and measurable business impact.
Responsibilities
- 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, 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.
Requirements
- 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.