Junior Data Scientist

Support the development of Cushman & Wakefield QIG’s analytical capabilities across commercial real estate markets across the Americas.

• 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

• 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

• Python, R, SQL
• ArcGIS, QGIS, GIS
• Azure, AWS
• ML/AI
• Census TIGER, IPUMS, LODES, NLCD, Overture Maps
• ACS, BLS
• TIGER

• 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
• Competitive pay

Location: Costa Mesa, CA (onsite)

Compensation: USD 114, per year