Junior Data Scientist

Support the development of Cushman & Wakefield QIG’s analytical capabilities across commercial real estate markets across the Americas. Responsibilities Run rigorous quantitative analysis on commercial real estate markets by synthesizing property, macroeconomic, and urban data to identify market trends and investment-relevant insights Use econometric and statistical techniques (time series modeling, regression, spatial econometrics, or similar) to address real estate and labor market research questions Integrate geospatial data and methods into analytics, including Census geographies, parcel data, land use classifications, walkability or transit metrics, and demographic overlays Help create novel datasets and indicators by specifying and building integrated data products that combine proprietary CRE data with public and third-party sources, partnering with the Head of Data Science & Geospatial Analytics Fulfill ad hoc analysis requests for Americas Research, the Global Think Tank, and senior stakeholders with clean, well-documented, and reproducible outputs Build and maintain automated data pipelines for ingesting, transforming, and storing CRE and macroeconomic datasets used in models and recurring analysis Maintain data integrity through validation, quality control, and structured data interfaces across QIG inputs and outputs Conduct exploratory data analysis and profiling on raw and processed datasets to validate pipeline outputs and flag anomalies or inconsistencies Partner with PRI (Property Research & Intelligence), TDS (Technology & Data Solutions), and the GIS team to support governance of time series and geospatial data as geography-based competitive sets evolve Act as a liaison to TDS by translating analytical requirements into engineering specifications, tracking data request status in the TDS backlog, and validating outputs against analytical expectations Create and maintain internal documentation for data sources, model architecture, data flows, and diagnostic procedures with field-level lineage and traceability Serve as a subject matter expert for integration and processing of internal, third-party vendor, and public datasets (including Census TIGER, IPUMS, LODES, NLCD, and Overture Maps), advising on cleaning, normalization, and suitable analytical applications Monitor third-party data product changes, assess fit to QIG requirements, and produce intake specifications when new sources are approved for integration Support adoption of emerging analytical technologies (including ML/AI and advanced data infrastructure patterns) through prototyping and coordination with TDS when appropriate Requirements Bachelor’s degree in a quantitative field: Economics, Data Science, Real Estate, Applied Economics, Geography, Urban Planning, or a closely related field; master’s degree preferred and doctoral degree a plus 2 to 6 years of experience in a research, analytical, or data science role, preferably in real estate, urban policy, planning, or economic research Strong quantitative methods experience including regression, time series analysis, spatial econometrics, or comparable approaches for real estate or urban economic questions Working knowledge of geospatial data and methods, including GIS tools (ArcGIS, QGIS, or programmatic approaches via R or Python), spatial data formats/concepts, and integrating geographic context into analysis Proficiency in Python and/or R for 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 used in urban and real estate research, including Census products (ACS, TIGER, LODES), BLS, IPUMS, or similar Ability to produce clean, well-documented, reproducible analytical work and communicate findings clearly to technical and non-technical audiences Comfort working independently and cross-functionally with engineering and research teams on iterative deliverables Intellectual interest in urban economics, commercial real estate markets, and the spatial dimensions of economic activity Comfort communicating analysis, methods, and related topics with partner teams and immediate management Technologies Python, R, SQL ArcGIS, QGIS, GIS Azure, AWS ML/AI Census TIGER, IPUMS, LODES, NLCD, Overture Maps ACS, BLS TIGER Benefits Health, vision, and dental insurance Flexible spending accounts Health savings accountsRetirement savings plans Life and disability insurance Paid and unpaid time away from work Competitive pay Location: Costa Mesa, CA (onsite) Compensation: USD 114,750 - 135,000 per year #J-18808-Ljbffr