数据科学家，房地产与办公
Data Scientist, Real Estate & Workplace
职位描述
我们正在招聘一名数据科学家，以支持房地产与办公环境（REW）团队。这是一个快速发展的全球团队，专注于打造能帮助OpenAI员工发挥最佳工作状态的办公环境，同时推动公司房地产和办公运营的扩展。我们的工作基于对人们如何使用空间和服务、在物理和数字环境中协作以及体验办公环境的理解。
REW的职责范围涵盖组合策略、设计与建设、空间规划、可持续性、办公体验和全球运营。你将能够自如地处理这个广泛且有时复杂的数据环境，并在各个领域建立可信赖的关系。这项工作为具有即时可见影响的重要决策提供依据——从团队的工作地点、空间和服务的分配方式，到哪些投资推进以及办公体验如何演变。这是一个高自主权的数据科学岗位，涵盖分析策略和实际执行。在AI原生分析的最前沿工作，你将帮助定义OpenAI办公运营的未来，而不是遵循既定的方案。你将塑造REW的数据科学路线图，识别预测、实验和优化可以带来影响的领域，并将业务重点转化为分析计划。你将负责面向利益相关者的执行层面，包括拥有由代理构建的仪表板、定期报告、模型和决策工具，以及分析需求、验证、采用和可衡量的业务影响。
在这个职位中，你将与财务、人员分析、IT和REW领导紧密合作。你将从问题的定义和优先级排序，到分析、建议、交付、采用和迭代，全程负责问题的解决，使工作产生可衡量的业务成果。
你将从事的工作包括：
- 全程负责模糊但影响重大的问题——从定义和优先级排序到交付、采用和迭代。
- 定义成功指标，建立用于人员、空间和投资决策的测量、预测、实验和优化框架。
- 开发并维护代理仪表板、报告、模型和决策工具，确保它们可信、受控且具备代理功能。
- 从办公传感器、协作工具、运营和财务系统中连接数据——同时识别并整合新的数据源——以指导关于空间、服务、员工体验和投资的决策。
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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 https://cdn.openai.com/policies/eeo-policy-statement.pdf.
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