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Summer Real Estate Data Science Jobs (NOW HIRING)

CoStar

Data Scientist

Richmond, VA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Commercial Real Estate industry professionals around the globe use CoStar to access the most ... Bachelor's degree in computer science, data analytics, statistics, machine learning, or related ...

CoStar Group

Data Scientist

Richmond, VA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Commercial Real Estate industry professionals around the globe use CoStar to access the most ... Bachelor's degree in computer science, data analytics, statistics, machine learning, or related ...

CoStar Group

Data Scientist

Richmond, VA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Commercial Real Estate industry professionals around the globe use CoStar to access the most ... Bachelor's degree in computer science, data analytics, statistics, machine learning, or related ...

Measurabl

Principal Product Manager

  • Medical

  • Dental

  • Retirement

  • PTO

Work closely with data science and engineering to translate real estate domain requirements into specs, models, and evaluation frameworks they can build and test against * Drive alignment across ...

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All JobsSummer Real Estate Data Science Jobs

Summer Real Estate Data Science information

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$37.5K

$122.7K

$196.5K

How much do summer real estate data science jobs pay per year?

As of Aug 17, 2026, the average yearly pay for summer real estate data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is the difference between Summer Real Estate Data Science vs Summer Real Estate Analyst?

AspectSummer Real Estate Data ScienceSummer Real Estate Analyst
Required CredentialsRelevant coursework in data science, statistics, or related fields; programming skills in Python or RBackground in real estate, finance, or economics; strong analytical skills
Work EnvironmentData-driven projects, coding, statistical analysis, often in tech or finance firmsMarket research, property analysis, client reports, often in real estate firms or agencies
Employer & Industry UsageTech companies, real estate platforms, investment firmsReal estate agencies, property management companies, investment firms

Summer Real Estate Data Science focuses on analyzing large datasets using programming and statistical methods to derive insights, often in tech or finance settings. In contrast, Summer Real Estate Analyst emphasizes market research and property analysis, typically within real estate firms. Both roles require analytical skills but differ in technical depth and work environment.

What cities are hiring for Summer Real Estate Data Science jobs?

Cities with the most Summer Real Estate Data Science job openings:

What are the most commonly searched types of Real Estate Data Science jobs?

The most popular types of Real Estate Data Science jobs are:

What states have the most Summer Real Estate Data Science jobs?

States with the most job openings for Summer Real Estate Data Science jobs include:

Summer Real Estate Data Science jobs near you

Real Estate Data Scientist - Remote

Harbor Freight Tools

Calabasas, CA • On-site, Remote

$98K - $147K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 22 days ago

Job description

The Real Estate Data Scientist is responsible for developing advanced analytical models and data-driven tools that support strategic real estate decisions across the organization. This role partners closely with Real Estate, Finance, Marketing, and Supply Chain teams to deliver predictive insights related to site selection, network optimization, sales forecasting, and market planning. This role incorporates advanced spatial modeling, geostatistics, and geospatial data engineering to evaluate trade areas, quantify market potential, and optimize network performance.
This position combines strong statistical modeling, data engineering, and business acumen to translate complex data into actionable recommendations. The Real Estate Data Scientist plays a critical role in advancing the organization's use of machine learning, automation, and predictive analytics to improve decision quality and scalability. This is a senior individual contributor role with no direct people management responsibility.
Duties and Responsibilities
  • Advanced Analytics & Predictive Modeling
    • Develop and deploy predictive models for site selection, sales forecasting, cannibalization, and market potential.
    • Build and maintain machine learning models using regression, classification, clustering, optimization, and spatial modeling techniques.
    • Apply spatial statistical methods (e.g., spatial regression, geographically weighted regression, spatial autocorrelation) to capture geographic variation in demand drivers.
    • Develop trade area and customer draw models (e.g., Huff/gravity models) to estimate market share and competitive impact.
    • Incorporate spatial features such as proximity, co-tenancy, demographics, traffic patterns, and nearby store performance into predictive models.
    • Design methodologies for forecasting store performance under various scenarios, including spatial and competitive effects.
    • Continuously monitor and improve model performance and accuracy. 
  • Data Engineering & Automation
    • Design scalable data pipelines integrating real estate, customer, demographic, sales, and geospatial datasets (parcel, census, traffic, mobility, POI data).
    • Perform geospatial data processing including geocoding, spatial joins, coordinate transformations, and spatial indexing (e.g., H3 or similar frameworks).
    • Write efficient SQL and Python workflows to automate recurring analyses, spatial feature engineering, and model refreshes.
    • Ensure data quality, consistency, and reproducibility across analytical outputs, including alignment of spatial boundaries and geographic hierarchies.
  • Real Estate Strategy & Decision Support
    • Partner with Real Estate teams to support site selection, market entry, relocations, and closures.
    • Develop drive-time and network-based trade area analyses to assess accessibility and market reach.
    • Conduct market coverage and white space analysis to identify expansion opportunities and underserved areas.
    • Build location-allocation and network optimization models to determine optimal site placement.
    • Quantify cannibalization and competitive effects using spatial overlap and proximity-based modeling.
    • Provide quantitative insights for Real Estate Committee (REC) evaluations and executive decisions.
    • Develop scoring frameworks and decision tools to prioritize opportunities.         
  • Visualization & Communication
    • Create clear, compelling visualizations and dashboards (Tableau, Power BI, or similar) to communicate insights.
    • Develop interactive geospatial visualizations including trade area maps, performance heatmaps, and market opportunity analyses.
    • Present analytical findings and recommendations to senior leadership and non-technical stakeholders.
  • Experimentation & Innovation
    • Design and execute experiments (A/B tests, quasi-experimental designs) to evaluate real estate strategies.
    • Implement geo-based testing frameworks (e.g., test vs. control markets) to measure impact of site decisions.
    • Apply causal inference methods (e.g., difference-in-differences, synthetic control) accounting for geographic spillovers.
    • Explore new data sources (e.g., mobility, foot traffic) and modeling techniques to enhance predictive capabilities.
    • Contribute to building a best-in-class real estate analytics capability.
  • Cross-Functional Collaboration
    • Work closely with GIS, Data Engineering, Finance, Marketing, and IT teams to align data and models.
    • Partner with GIS teams to ensure alignment between spatial analysis, mapping, and production data pipelines.
    • Translate business problems into analytical solutions and actionable insights.
Scope
  • Staff supervision and development:  No
  • Decision making: 
    • Develops models and analytical frameworks used in strategic decision-making
  • Travel:  Up to 10%
  • Flex Designation:  Anywhere

The anticipated salary range for this position is $98,500-$147,800 depending on location, knowledge, skills, education and experience. This position is also eligible for an annual discretionary bonus. In addition, we offer comprehensive and competitive benefits to Associates (and their families) such as medical, dental, vision, life insurance, short-term and long-term disability. Eligible Associates are able to enroll in our company's 401k plan. Associates will accrue paid time off up to 236 hours per year (inclusive of PTO, floating holidays, and paid holidays). Paid sick time up to 80 hours per year unless otherwise required by law.

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