Junior Data Scientist

Job Title Junior Data Scientist Job Description Summary 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. This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate is a practitioner who thinks first like an economist, real estate analyst, or quantitative urban planner, and who brings the technical skills to build and operate the data infrastructure their own work requires. This is not primarily an engineering role, though the ideal candidate will possess data engineering knowledge, skills, and abilities. The Analyst will spend most of their time doing substantive analytical and research work: synthesizing complex datasets, identifying market patterns and anomalies, and producing outputs that inform Lumen Dynamics’s House View, including elements that are unique to QIG, and related analytical products for key clients. At the same time, the candidate should be comfortable constructing and maintaining data pipelines, working fluently in Python and/or R and SQL, and collaborating closely with Technology & Data Solutions (TDS) as a knowledgeable and credible partner. Job Description Key Responsibilities Real Estate & Urban Economic Analysis (45%) 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. Data Engineering & Pipeline Maintenance (35%) Build andmaintainautomated data pipelines for ingesting, transforming, and storing CRE and macroeconomic datasets used in analytical modelsand reoccurring analysis. Ensure data integrity and consistency across QIG inputs and outputs through validation, quality control procedures, and structured data interfaces. Perform exploratory data analysis and profiling on raw and processed datasets tovalidatepipeline outputs andidentifyanomalies or inconsistencies. Partner with PRI (Property Research & Intelligence), TDS (Technology & Data Solutions), and the GIS team to ensure governance of time series and geospatial data, particularly as geography-based competitive sets evolve. Serve as a knowledgeable liaison to TDS: translating analytical requirements into engineering specifications, tracking the status of data requests in the TDS backlog, and validating outputs against analytical expectations. Documentation, Integration & Infrastructure (20%) Develop andmaintaininternal documentation covering data sources, model architecture, data flows, and diagnostic procedures, with attention to field-level lineage and traceability. Serve as the team's subject matter expert on integration and processing of internal, third-party vendor, and public datasets (e.g., Census TIGER, IPUMS, LODES, NLCD, Overture Maps), and advise on cleaning, normalization, andappropriate analyticalapplications. Monitor the evolution of third-party data products; assess their fit against QIG analytical requirements and produce intake specifications when new sources are approved for integration. Support the adoption of emerging analytical technologies (including ML/AI methods and advanced data infrastructure patterns) through hands-on prototyping and coordination with TDS whereappropriate. Qualifications Bachelor’s degree inEconomics,Data Science,Real Estate, Applied Economics, Geography,UrbanPlanningor anyclosely related field with quantitative emphasis.A master’s degree ispreferredand adoctoral degree is a plus. 2 to 6 yearsof experience ina 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. Working kno