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Evening Real Estate Data Science Jobs (NOW HIRING)

Ascent Developer Solutions

Machine Learning Engineer

Los Angeles, CA · On-site

$123K - $148K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Analyze public records and other real estate data using NLP and machine learning techniques to ... Strong data science skills with AI/ML related Python libraries such as PyTorch, TensorFlow, and ...

KidStrong

Real Estate Manager

Frisco, TX · On-site

  • Dental

  • Vision

  • Retirement

  • PTO

KidStrong is a science based program for kids ages 1-11 that uses certified coaches to help kids ... Supports the Franchise Development team by validating market and territory data and exhibits for ...

KidStrong

Real Estate Manager

Frisco, TX · On-site

  • Dental

  • Vision

  • Retirement

  • PTO

KidStrong is a science based program for kids ages 1-11 that uses certified coaches to help kids ... Supports the Franchise Development team by validating market and territory data and exhibits for ...

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

Data Scientist

Richmond, VA

  • 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

  • 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 ...

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

As of Aug 15, 2026, the average yearly pay for evening 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 an evening real estate data scientist?

An Evening Real Estate Data Scientist is a professional who applies data science techniques to analyze and interpret real estate data, typically working during evening hours. Their responsibilities often include examining property trends, evaluating investment opportunities, and creating predictive models to assist real estate companies or clients in making informed decisions. Working in the evenings can accommodate clients across different time zones or support organizations that operate outside standard business hours. These data scientists need strong analytical, statistical, and programming skills, often using tools like Python, R, and SQL. Their insights help optimize property valuation, marketing strategies, and operational efficiencies in the real estate sector.

How is data science used in real estate?

In real estate, data science is used by professionals such as data analysts and real estate data scientists to analyze market trends, predict property values, and assess investment risks. They utilize tools like machine learning algorithms and geographic information systems (GIS) to make data-driven decisions and optimize property listings and pricing strategies.

What are the typical collaboration dynamics for an evening real estate data science role?

In an Evening Real Estate Data Science role, you will often work closely with real estate analysts, property managers, and IT professionals to deliver data-driven insights outside of standard business hours. This unique schedule allows you to process and analyze large datasets with minimal interruptions while providing timely updates for teams starting their day. Regular communication is maintained via digital channels, and you may participate in virtual meetings or handoff sessions to ensure seamless workflow continuity. Collaboration is key, so strong remote communication and documentation skills are essential for success in this role.

What are the key skills and qualifications needed to thrive as an evening real estate data scientist?

To excel as an Evening Real Estate Data Scientist, you need strong analytical skills, experience in statistical modeling, and a background in real estate, typically supported by a degree in data science, computer science, or a related field. Proficiency with tools like Python, R, SQL, and real estate analytics platforms such as CoStar or Zillow is essential, as well as familiarity with machine learning frameworks. Excellent problem-solving, communication, and time management skills help you translate complex data into actionable business insights, especially when working independently or on flexible evening schedules. These competencies are critical for providing accurate, timely analysis that supports strategic decision-making in the real estate sector.

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

Cities with the most Evening 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 Evening Real Estate Data Science jobs?

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

Evening 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

This job post has expired today. Applications are no longer accepted.

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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