Commercial Real Estate Data Jobs

1 job found

1d ago

Junior Data Scientist

Cushman & Wakefield Costa Mesa, CA

Costa Mesa, CA

1d ago

$115k - $135k/yr Full time Cloud Platform Cloud Platforms Commercial Real Estate

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Job Description

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 accounts
Retirement savings plans
Life and disability insurance
Paid and unpaid time away from work
Competitive pay

Location: Costa Mesa, CA (onsite)

Compensation: USD 114,750 - 135,000 per year

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