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Flexible Real Estate Data Science Jobs (NOW HIRING)

Avid Core

Real Estate Data Analyst

Washington, DC · On-site

$55K - $75K/yr

Avid Core is seeking a Real Estate Data Analyst to support a federal contract involving land and ... Flexible paid time off * Generous bonus program based on firm and individual performance * An ...

KidStrong

Real Estate Manager

Frisco, TX · On-site

Flexible schedule Are you looking for that workplace where you can be part of a fun, energetic, and ... KidStrong is a science based program for kids ages 1-11 that uses certified coaches to help kids ...

PLACE

Flexible Real Estate Career

Virginia Beach, VA · On-site

$100K - $180K/yr

Summary Take Charge of Your Career Path You entered real estate seeking independence... But over time, it began to feel like this: * Always on call * Constantly available * Endless grind This isn't ...

KidStrong

Real Estate Manager

Frisco, TX · On-site

Flexible schedule Are you looking for that workplace where you can be part of a fun, energetic, and ... KidStrong is a science based program for kids ages 1-11 that uses certified coaches to help kids ...

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Flexible Real Estate Data Science information

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$37.5K

$122.7K

$196.5K

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

As of Aug 3, 2026, the average yearly pay for flexible 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 Flexible Real Estate Data Science vs Real Estate Data Analyst?

AspectFlexible Real Estate Data ScienceReal Estate Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; proficiency in programming languages like Python or RDegree in Real Estate, Economics, or related field; proficiency in Excel and data visualization tools
Work EnvironmentCollaborative teams, often in tech-driven or real estate firms, with focus on modeling and predictive analyticsOffice-based, analyzing real estate data, preparing reports, and supporting decision-making
Employer & Industry UsageReal estate tech companies, property management firms, investment firmsReal estate agencies, brokerage firms, property management companies

Flexible Real Estate Data Science involves advanced data modeling, machine learning, and predictive analytics to inform real estate decisions. In contrast, a Real Estate Data Analyst primarily focuses on data collection, reporting, and basic analysis. Both roles require strong analytical skills, but the data scientist role demands more technical expertise in programming and modeling techniques.

More about Flexible Real Estate Data Science jobs
What cities are hiring for Flexible Real Estate Data Science jobs? Cities with the most Flexible 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 Flexible Real Estate Data Science jobs? States with the most job openings for Flexible Real Estate Data Science jobs include:
What job categories do people searching Flexible Real Estate Data Science jobs look for? The top searched job categories for Flexible Real Estate Data Science jobs are:
Flexible Real Estate Data Science jobs near you
Infographic showing various Flexible Real Estate Data Science job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

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 9 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.
Requirements
Education and Experience
Education Requirements
  • Bachelor's degree in data science, Statistics, Economics, Mathematics, Computer Science, or related field from a nationally recognized institution. Master's degree preferred
Years of Experience
  • 5 to 8 plus years of experience in data science, analytics, or quantitative modeling, preferably in retail, real estate, consulting, or related fields.
Skills
  • Strong proficiency in Python (pandas, scikit-learn, etc.) and SQL for data analysis and modeling.
  • Experience building predictive models and applying statistical techniques to business problems.
  • Experience working with cloud-based platforms (Databricks, Snowflake, Azure)
  • Familiarity with geospatial analysis and GIS concepts, including trade area modeling, spatial statistics, and network-based analysis (experience with ESRI or similar tools preferred).
  • Experience working with large, complex datasets from multiple sources.
  • Experience with BI and visualization tools (Tableau, Power BI, etc.).
  • Strong understanding of experimental design and statistical inference.
  • Ability to communicate complex analyses clearly to non-technical stakeholders.
  • Strong problem-solving skills and business acumen.
Physical Requirements
Corporate - Remote - General office environment requiring ability to:
  • Stand, walk, sit for extended periods of time .
  • Speak and listen to others in person and over the phone and video conferencing.
  • Use keyboard and read from computer screen and reports.
  • The ability to lift up to 15 lbs.
Safety
Must be able to perform this job safely in accordance with standard operating procedures and good manufacturing practices, without endangering the health or safety of self or others.
About Harbor Freight Tools
We're a 45 year-old, $8 billion national tool retailer with the energy, enthusiasm, and growth potential of a start-up. We have over 1,600 stores in 48 states across the country and are opening several new locations every week. We offer our customers more than 7,000 tools and accessories, from hand tools and generators to air and power tools, from shop equipment to automotive tools. We provide our customers with the right tool for the right job at the right price, always delivering quality and value.

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