Junior Data Scientist

Experteer Overview In this role you will support Cushman & Wakefield’s Quantitative Insight Group by delivering rigorous, insight-driven analysis of commercial real estate markets across the Americas. You will work under the Head of Data Science and Geospatial Analytics to build and operate the data infrastructure needed for analytical outputs. The role blends economic and urban analysis with hands-on data engineering, prioritizing reproducible research and cross-functional collaboration. You will contribute to market views and analytical products that inform clients and internal teams, leveraging geospatial and macro data to reveal trends and anomalies. This is a practical, data-driven position centered on to Compensation / Benefits * Conduct rigorous quantitative analysis of commercial real estate markets, integrating property, macroeconomic, and urban data to identify trends and insights * Apply econometric and statistical methods (time series, regression, spatial econometrics) to real estate questions for QIG research outputs * Incorporate geospatial data, workflows, and inputs (Census geographies, parcel data, walkability, transit metrics, demographic overlays) to enrich market analysis * Develop novel datasets and indicators by integrating proprietary CRE data with public/third-party sources * Support ad hoc analytical requests from Americas Research and senior stakeholders with clean, reproducible outputs * Build and maintain automated data pipelines for ingesting, transforming, and storing CRE and macro datasets used in models * Ensure data integrity through validation and quality control across inputs/outputs * Collaborate with PRI, TDS, and GIS teams to govern time series and geospatial data; translate analytics requirements into engineering specs * Produce internal documentation detailing data sources, models, data flows, and diagnostics; act as SME for data integration and processing of public, vendor, and internal datasets * Prototype and coordinate adoption of emerging analytical technologies (ML/AI, advanced data infra) with TDS where appropriate Tasks * Bachelor’s degree in Economics, Data Science, Real Estate, Applied Economics, Geography, Urban Planning or related quantitative field * 2-6 years of research, analytical, or data science experience in real estate, urban policy, planning, or economic research * Strong command of quantitative methods: regression, time series, and spatial econometrics applied to real estate/urban questions * Experience with geospatial data and GIS tools (ArcGIS, QGIS) and programmatic approaches in Python or R; familiarity with GIS data formats * Proficiency in Python and/or R for analysis and modeling; working knowledge of SQL; familiarity with cloud platforms (Azure, AWS) and version control is a plus * Experience with public datasets used in urban/real estate research (Census ACS/TIGER/LODES, BLS, IPUMS) * Ability to produce clear, well-documented, reproducible analyses and communicate findings to technical and non-technical audiences * Comfort working in a cross-functional environment with engineering and research teams on iterative deliverables * Genuine interest in urban economics, CRE markets, and the spatial dimensions of economic activity * Strong communication skills to discuss analyses and methods with related teams and management Key requirements * health, vision, and dental insurance * flexible spending accounts * health savings accounts * retirement savings plans * life and disability insurance * paid and unpaid time away from work

_ emerging analytical technologies (ML/AI, advanced data infra) with TDS where appropriate Tasks * Bachelor’s degree in Economics, Data Science, Real Estate, Applied Economics, Geography, Urban Planning or related quantitative field * 2-6 years of research, analytical, or data science experience in real estate, urban policy, planning, or economic research * Strong command of quantitative methods: regression, time series, and spatial econometrics applied to real estate/urban questions * Experience with geospatial data and GIS tools (ArcGIS, QGIS) and programmatic approaches in Python or R; familiarity with GIS data formats * Proficiency in Python and/or R for analysis and modeling; working knowledge of SQL; familiarity with cloud platforms (Azure, AWS) and version control is a plus * Experience with public datasets used in urban/real estate research (Census ACS/TIGER/LODES, BLS, IPUMS) * Ability to produce clear, well-documented, reproducible analyses and communicate findings to technical a3 _ non-technical audiences * Comfort working in a cross-functional environment with engineering and research teams on iterative deliverables * Genuine interest in urban economics, CRE markets, and the spatial dimensions of economic activity * Strong communication skills to discuss analyses and methods with related teams and management Key requirements * health, vision, and dental insurance * flexible spending accounts * health savings accounts * retirement savings plans * life and disability insurance * paid and unpaid time away from work