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Freelance Real Estate Data Science Jobs (NOW HIRING)

MIG Real Estate Services, LLC

Senior Data Analyst

$88K - $111K/yr

MIG Real Estate is looking for a Senior Data Analyst to join our growing real estate team ... Bachelor's degree in a field related to data science, or equivalent practical experience. * Minimum ...

Parker's Kitchen

Real Estate Analyst

Savannah, GA · On-site

The ideal candidate thrives in a data-driven environment, communicates insights clearly, and has a strong understanding of the convenience store, fuel retail, or broader retail real estate landscape.

Cushman & Wakefield

Junior Data Scientist

Boston, MA

This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate is a practitioner who thinks first like an economist, real estate analyst, or quantitative urban ...

Cushman & Wakefield

Junior Data Scientist

Austin, TX

This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate is a practitioner who thinks first like an economist, real estate analyst, or quantitative urban ...

Cushman & Wakefield

Junior Data Scientist

Denver, CO

This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate is a practitioner who thinks first like an economist, real estate analyst, or quantitative urban ...

Cushman & Wakefield

Junior Data Scientist

Denver, CO

This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate is a practitioner who thinks first like an economist, real estate analyst, or quantitative urban ...

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How much do freelance real estate data science jobs pay per hour?

As of Jul 6, 2026, the average hourly pay for freelance real estate data science in the United States is $20.27, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $22.36 per hour, depending on experience, location, and employer.

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

To thrive as a Freelance Real Estate Data Scientist, you need a strong background in statistics, data analysis, and domain expertise in real estate, often supported by a degree in data science or a related field. Proficiency in programming languages like Python or R, familiarity with real estate databases, and experience with machine learning tools such as scikit-learn or TensorFlow are highly valuable. Excellent problem-solving abilities, effective communication, and self-management skills help you deliver actionable insights and manage multiple client projects. These skills ensure you can analyze complex property markets, provide data-driven recommendations, and build trust with clients in a competitive freelance environment.

Is 40 too late for data science?

For a freelance real estate data science role, starting a career at 40 is feasible as the field values skills, experience, and the ability to work with data analysis tools like Python or R. Many professionals transition into data science later in life, and continuous learning through online courses or certifications can help build relevant expertise regardless of age.

Can I do freelancing with data science?

Freelance real estate data science is a viable career option, allowing professionals to analyze property data, develop models, and provide insights independently. Success typically requires skills in data analysis, programming, and familiarity with real estate markets, along with tools like Python or R. Freelancers often work on project-based contracts, setting their schedules and rates based on expertise and client needs.

What is freelance real estate data science?

Freelance real estate data science involves using data analysis, statistical modeling, and machine learning techniques to help real estate professionals make informed decisions. Freelancers in this field work independently with clients such as real estate agencies, investors, or property managers to analyze market trends, predict property values, and optimize investment strategies. They often handle tasks like data cleaning, visualization, and the development of predictive models tailored to real estate data. This role requires a strong background in data science, familiarity with real estate markets, and the ability to communicate complex findings to clients.

How do freelance real estate data scientists typically collaborate with clients and other professionals during a project?

Freelance real estate data scientists often work remotely and maintain close communication with clients, project managers, and other stakeholders through virtual meetings and collaborative platforms. They are responsible for clarifying project goals, sharing data analysis progress, and incorporating feedback throughout the process. Collaboration may also include working with real estate agents, financial analysts, or software developers to ensure accurate data integration and actionable insights. Building strong client relationships and proactively addressing questions enhances project outcomes and can lead to repeat business or referrals.

What is the hourly rate for a freelance data scientist?

The hourly rate for a freelance real estate data scientist typically ranges from $50 to $150, depending on experience, skills in data analysis and machine learning, and project complexity. Rates can vary based on location, specialization, and client requirements.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or data. For a freelance real estate data scientist, this means focusing on the most impactful data features or models that drive the majority of insights or predictions, optimizing time and resources. Understanding this principle helps prioritize tasks such as feature selection and model tuning for efficient analysis.
What cities are hiring for Freelance Real Estate Data Science jobs? Cities with the most Freelance 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 Freelance Real Estate Data Science jobs? States with the most job openings for Freelance Real Estate Data Science jobs include:
Freelance Real Estate Data Science jobs near you

Senior Data Analyst

MIG Real Estate Services, LLC

Remote

$88K - $111K/yr

Full-time

Posted 29 days ago

Job description

MIG Real Estate is looking for a Senior Data Analyst to join our growing real estate team. Reporting to the CTO, you will be responsible for creating and operating a comprehensive data, reporting and visualization platform to support our acquisition, operation, and disposition of real estate assets. You will serve as a bridge between the business and the technical teams, and you will be a data analytics expert, including adopting and sharing best practice about collecting, cleaning, and organizing data to maximize our potential use of machine learning and AI. You will need a high level of technical and business acumen, excellent communication skills, and a demonstrated ability to work in a fast-paced business environment.
About The Job
At MIG Real Estate, data drives decision-making, and our team defines and interprets data to provide recommendations and perspectives to management and their teams. Our objective is to ensure that we have meaningful data and insights to make thoughtful decisions, most of which have a direct impact on our business. We also seek to build data fluency throughout the company.
In this role, you will work with a small team to expand and optimize our Microsoft Azure / Fabric data environment, including data pipeline architecture and Power BI-based dashboards and reports. The ideal candidate is an experienced data wrangler who enjoys working with multiple data sources, optimizing data architecture and semantic models, and working with users to ensure their business requirements are met using Excel and Power BI, including ad hoc queries and analysis.
As a key member of a small, growing team, you will also support other IT initiatives, including SharePoint and Teams enhancements, and tools to support automation of workflows and better collaboration.
Responsibilities
  • Manage the infrastructure for efficient ETL pipelines from a wide variety of data sources, primarily using SQL.
  • Build analytics tools that utilize the data pipeline to provide actionable insights into key business performance metrics.
  • Work with stakeholders across the firm to assist with data-related technical issues and support their data infrastructure needs.
  • Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
  • Work with real estate colleagues to develop analytics and reporting to support our operations.
  • Build and maintain AI-assisted workflows and reporting automations in collaboration with the automation team.
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Take on projects to support development of strategy and measure its effectiveness.
  • Own and govern shared Power BI semantic models deployed in Microsoft Fabric workspaces, ensuring accuracy, performance, and accessibility for business users.
  • Partner with the data engineering and automation team members on pipeline design, ETL and semantic model optimization, warehouse structure, and delivery of analytics-ready datasets.

Requirements
  • Advanced experience developing in Power BI and DAX, including ownership of shared semantic models and report governance in a multi-user environment. Tabular Editor experience strongly preferred.
  • Hands-on experience with Microsoft Fabric, including lakehouses, warehouses, and Fabric workspace administration.
  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  • Experience integrating Power BI with Excel, including CUBEVALUE-based reporting and Excel-as-reporting-layer patterns.
  • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
  • Familiarity with financial accounting and cost accounting concepts.
  • Strong analytic skills related to working with unstructured datasets (e.g., media, documents).
  • Familiarity with the mechanics of data preparation, data handling, data warehousing, and similar projects.
  • A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
  • Strong project management and organizational skills.
  • Experience using and managing SharePoint sites and document libraries.
  • Working knowledge of multifamily and commercial real estate operations, including key performance metrics (NOI, occupancy, same-store variance, rent roll) and data providers (CoStar, RealPage, Argus Enterprise).
  • Familiarity with Yardi Voyager data structures, Argus Enterprise exports, or comparable property management and asset management systems strongly preferred.
  • Willingness to travel for periodic company meetings.

Qualifications
  • Bachelor's degree in a field related to data science, or equivalent practical experience.
  • Minimum of 4-5 years in a data analytics, visualization, and reporting role, with demonstrated ownership of production analytics environments and management of key stakeholders.

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