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About the Role

This role sits at the intersection of real estate economics, urban analysis, and data science. The Junior Data Scientist supports the Quantitative Insight Group (QIG) by producing rigorous, insight-driven work on commercial real estate markets across the Americas, reporting to the Head of Data Science and Geospatial Analytics.

Responsibilities

• Conduct quantitative analysis on commercial real estate markets by synthesizing property, macroeconomic, and urban data.
• Apply econometric and statistical methods such as time series modeling and regression to real estate and labor market questions.
• Integrate geospatial data and methods into analytical workflows using Census geographies, parcel data, and demographic overlays.
• Develop novel datasets and indicators to advance analytical capabilities.
• Support ad hoc analytical requests from research and senior stakeholders with well-documented, reproducible outputs.
• Build and maintain automated data pipelines for ingesting, transforming, and storing CRE and macroeconomic datasets.
• Perform exploratory data analysis and quality control to ensure data integrity and identify anomalies.
• Partner with internal teams to ensure governance of time series and geospatial data.
• Serve as a liaison to Technology & Data Solutions to translate analytical requirements into engineering specifications.
• Maintain documentation covering data sources, model architecture, and data flows.
• Serve as a subject matter expert on the integration of internal, third-party, and public datasets.
• Monitor and assess third-party data products for integration suitability.
• Support the adoption of emerging analytical technologies through prototyping.

Requirements

• Bachelor’s degree in Economics, Data Science, Real Estate, Applied Economics, Geography, Urban Planning, or a related quantitative field.
• 2 to 6 years of experience in a research, analytical, or data science role.
• Strong command of quantitative methods including regression, time series analysis, and spatial econometrics.
• Working knowledge of geospatial data and GIS tools such as ArcGIS or QGIS.
• Proficiency in Python and/or R for data analysis, modeling, and pipeline construction.
• Working knowledge of SQL.
• Experience with public datasets such as Census products, BLS, or IPUMS.
• Ability to communicate findings clearly to technical and non-technical audiences.
• Ability to work independently and in cross-functional environments.

Skills

• Econometrics
• Statistical modeling
• Spatial analysis
• Data engineering
• Python
• R
• SQL
• GIS tools
• Data pipeline construction
• Exploratory data analysis

Work Type

• Full-time

Experience Level

• 2 to 6 years

Education Level

• Bachelor’s degree required
• Master’s degree preferred
• Doctoral degree is a plus

Salary/Compensations

• $114,750 - $135,000

Benefits

• Health insurance
• Vision insurance
• Dental insurance
• Flexible spending accounts
• Health savings accounts
• Retirement savings plans
• Life insurance
• Disability insurance
• Paid and unpaid time away from work

About the Company

• Cushman & Wakefield (NYSE: CWK) is a global leader in real estate services with 52,000 employees in nearly 400 offices across 60 countries.
• The firm has over 100 years of history and generated $9.5 billion in revenue in 2023.

Equal Opportunity

• Cushman & Wakefield is an Equal Opportunity employer to all protected groups, including protected veterans and individuals with disabilities.
• Discrimination of any type will not be tolerated.