Junior Data Scientist
About the role
This role sits at the intersection of real estate economics, urban analysis, and data science. The Junior Data Scientist will support the development and evolution of Cushman and Wakefield Quantitative Insight Group’s (QIG) analytical capabilities by producing rigorous, insight-driven work on commercial real estate markets across the Americas.
Responsibilities
Conduct rigorous quantitative analysis on commercial real estate markets, synthesizing property, macroeconomic, and urban data to surface market trends, structural shifts, and investment-relevant insights.
Apply econometric and statistical methods (time series modeling, regression, spatial econometrics, or similar) to real estate and labor market questions in support of QIG research products.
Integrate geospatial data and methods into analytical workflows: working with Census geographies, parcel data, land use classifications, walkability or transit metrics, demographic overlays, and similar inputs to enrich market analysis.
Contribute to the development of novel datasets and indicators that advance QIG's analytical edge, including working closely with the Head of Data Science & Geospatial Analytics to specify and build integrated data products combining proprietary CRE data with public and third-party sources.
Support the QIG team on ad hoc analytical requests from Americas Research, the Global Think Tank, and senior stakeholders, producing clean, well-documented, and reproducible outputs.
Requirements
Bachelor’s degree in Economics, Data Science, Real Estate, Applied Economics, Geography, Urban Planning or any closely related field with quantitative emphasis.
A master’s degree is preferred and a doctoral degree is a plus.
2 to 6 years of experience in a research, analytical, or data science role, preferably in a real estate, urban policy, planning, or economic research context.
Strong command of quantitative methods: regression, time series analysis, spatial econometrics, or comparable approaches applied to real estate or urban economic questions.
Familiarity with geospatial data and methods: experience with GIS tools (ArcGIS, QGIS, or programmatic approaches via R or Python), familiarity with spatial data formats and concepts, and comfort integrating geographic context into analysis.
Proficiency in Python and/or R for data analysis, modeling, and pipeline construction; working knowledge of SQL.
Familiarity with cloud platforms (Azure, AWS) and version control is a plus.
Experience working with public datasets commonly used in urban and real estate research: Census products (ACS, TIGER, LODES), BLS, IPUMS, or similar.
Qualifications
Genuine intellectual interest in urban economics, commercial real estate markets, and the spatial dimensions of economic activity.
Comfortable operating in a cross-functional environment, working both independently and alongside engineering and research teams on iterative deliverables.
Skills
Python and/or R programming.
SQL database management.
Geospatial data analysis using GIS tools.
Experience with cloud platforms (Azure, AWS).
Experience with public datasets commonly used in urban and real estate research.
Benefits
Cushman & Wakefield provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health, vision, and dental insurance, flexible spending accounts, health savings accounts, retirement savings plans, life, and disability insurance programs, and paid and unpaid time away from work.
The company will not pay less than minimum wage for this role.
Pay
$ 114,750.00 - $135,000.00
Schedule
Full-time