Data Scientist, Real Estate & Workplace
The Data Scientist will shape analytics strategy and deliver forecasting, experimentation, optimization, dashboards, models, and decision tools for Real Estate & Workplace operations. The role requires strong applied statistics, causal inference, SQL, Python, stakeholder communication, and comfort working with ambiguous operational data.
About the job
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, while identifying and integrating novel data sources.
- 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.
- Fluency in SQL and Python.
- Ability to turn messy, broad datasets into high-impact decisions and measurable outcomes.
- 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.
Skills
Python, SQL, Applied Statistics, Causal Inference, Forecasting, Model Evaluation, Optimization, Experimentation, Data Visualization, Operational Automation, Workplace Sensors, Collaboration Technologies
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