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Assistant Real Estate Data Science Jobs (NOW HIRING)

Guggenheim

Real Estate Analyst

Frisco, TX · On-site

They will assist the Real Estate Managers/Directors in researching market potential, identifying ... Working knowledge of real estate data and analytics platforms including: Placer.ai, Sites USA ...

Avid Core

Real Estate Data Analyst

Washington, DC

$55K - $75K/yr

Avid Core is seeking a Real Estate Data Analyst to support a federal contract involving land and property acquisition through eminent domain. This role will analyze ownership and acquisition data ...

Timely Searches LLC

Real Estate Data Specialist

Ravenna, OH

$15.50 - $20.75/hr

Entry-Level Real Estate Data Specialist Timely Searches LLC Ravenna, Ohio Timely Searches LLC in Ravenna, Ohio is seeking a reliable and detail-oriented Entry-Level Real Estate Data Specialist. This ...

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 property acquisition through eminent domain. This role will analyze ownership and acquisition data ...

Avid Core

Real Estate Data Analyst

Washington, DC · On-site

Avid Core is seeking a Real Estate Data Analyst to support a federal contract involving land and property acquisition through eminent domain. This role will analyze ownership and acquisition data ...

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 property acquisition through eminent domain. This role will analyze ownership and acquisition data ...

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Assistant Real Estate Data Science information

Is AI taking real estate agents jobs?

AI is transforming real estate by automating tasks such as data analysis, property valuation, and customer inquiries, which can enhance efficiency for roles like Assistant Real Estate Data Scientist. However, AI is generally seen as a tool to support agents rather than replace them entirely, emphasizing the need for skills in data analysis, machine learning, and client interaction. Real estate professionals who adapt to these technologies can improve their service and stay competitive in the evolving market.

What does an Assistant Real Estate Data Science professional do?

An Assistant Real Estate Data Science professional supports the analysis and interpretation of real estate data to help guide business decisions. They assist in collecting, cleaning, and organizing large datasets related to property values, market trends, and customer behavior. Their work often involves using statistical methods and machine learning tools to generate insights, create reports, and support predictive modeling. This role is essential for helping real estate companies make data-driven choices in buying, selling, or managing properties.

What is the highest paid job in data science?

The highest paid roles in data science are often senior positions such as Lead Data Scientist, Machine Learning Director, or Chief Data Officer, with salaries exceeding $150,000 annually. These roles typically require advanced skills in machine learning, big data tools, and strategic decision-making, and they are found in large corporations or tech companies.

What are the key skills and qualifications needed to thrive as an Assistant Real Estate Data Scientist, and why are they important?

To thrive as an Assistant Real Estate Data Scientist, you need strong analytical skills, a solid understanding of statistical methods, and a degree in data science, statistics, computer science, or a related field. Experience with tools like Python, R, SQL, and familiarity with real estate databases or property management systems is typically required. Excellent problem-solving abilities, attention to detail, and strong communication skills help in interpreting data and conveying insights to stakeholders. These skills are crucial for providing actionable data-driven recommendations that support real estate business strategies and decision-making.

How does an Assistant Real Estate Data Science professional typically collaborate with other departments within a real estate firm?

As an Assistant Real Estate Data Science professional, you will regularly partner with teams such as sales, marketing, finance, and property management. Your role often involves translating complex data analyses into actionable insights that help these departments make informed decisions about investments, pricing strategies, and customer targeting. You may also participate in cross-functional meetings to align on project goals and ensure that data-driven solutions support broader business objectives. Effective communication and the ability to explain technical findings to non-technical colleagues are key aspects of success in this collaborative environment.

Is 40 too late for data science?

For an Assistant Real Estate Data Science role, age is not a barrier; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and data analysis, which can be developed through online courses or certifications at any age.

Is 30 too late for data science?

For an Assistant Real Estate Data Science role, starting a career in data science at age 30 is feasible, as many professionals transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and domain knowledge, often through online courses or certifications, regardless of age.
What cities are hiring for Assistant Real Estate Data Science jobs? Cities with the most Assistant 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 Assistant Real Estate Data Science jobs? States with the most job openings for Assistant Real Estate Data Science jobs include:
Assistant Real Estate Data Science jobs near you
Infographic showing various Assistant Real Estate Data Science job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 99% Physical, and 1% Remote job distribution.
Real Estate Data Scientist - Remote

Real Estate Data Scientist - Remote

Harbor Freight Tools

Calabasas, CA • On-site, Remote

$98K - $147K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 25 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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