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Remote Geospatial Data Scientist Jobs in California

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

Data Scientist

Santa Cruz, CA ยท Remote

$130K - $170K/yr

Fullpower-AI delivers a complete B2B IoT platform for AI-powered algorithms, remote contactless ... Fullpower is seeking a passionate, team-oriented, and self-motivated Data Scientist interested in ...

Remote/Hybrid Brief Overview of the Our Client is seeking a highly skilled Data Scientist to leverage large volumes of data using modern tools and technologies to uncover insights, build predictive ...

Data Scientist

San Francisco, CA ยท On-site +1

$194K/yr

Position is 100% remote. Salary: $194,834 per year. Requirements: * Master's degree in Data Science, Statistics, Business Analytics, or a related field, plus 4 years of experience as a Data Scientist ...

Data Scientist

San Francisco, CA ยท On-site +1

$160K - $200K/yr

This is a remote position, but we do have an office in San Fransisco. You will be the first data scientist on the team working through and building models from scratch that will be pivotal for our ...

Data Scientist

San Francisco, CA ยท Remote

$160K - $200K/yr

This is a remote position, but we do have an office in San Fransisco. You will be the first data scientist on the team working through and building models from scratch that will be pivotal for our ...

NFL Data Scientist

San Francisco, CA ยท On-site +1

$140K/yr

Data Science is at the core of our business, so this team has true ownership and impact over ... This position is remote from the USA. Duties: * Ideate, develop and improve machine learning and ...

Soccer Data Scientist

San Francisco, CA ยท On-site +1

$130K/yr

Data Science is at the core of our business, so this team has true ownership and impact over ... This position is remote from the USA. Duties: * Ideate, develop and improve machine learning and ...

Data Scientist

San Francisco, CA ยท On-site +1

$194K/yr

Position is 100% remote. Salary: $194,834 per year. Requirements: * Master's degree in Data Science, Statistics, Business Analytics, or a related field, plus 4 years of experience as a Data Scientist ...

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Remote Geospatial Data Scientist information

What is the difference between Remote Geospatial Data Scientist vs Remote GIS Analyst?

AspectRemote Geospatial Data ScientistRemote GIS Analyst
Required CredentialsBachelor's/Master's in GIS, Geography, Data Science; experience with spatial analysisBachelor's in GIS, Geography, or related field; proficiency in GIS software
Work EnvironmentData analysis, modeling, programming, and spatial data interpretationMapping, data management, spatial data visualization
Employer & Industry UsageTech companies, environmental agencies, urban planningGovernment agencies, utilities, environmental firms
Common Search & ComparisonFocuses on data science and modelingFocuses on mapping and spatial data management

The Remote Geospatial Data Scientist primarily works on advanced spatial data analysis, modeling, and programming to extract insights from geospatial data. In contrast, the Remote GIS Analyst focuses on mapping, data management, and spatial visualization. Both roles require GIS knowledge but differ in their core responsibilities and skill sets.

How do Remote Geospatial Data Scientists typically collaborate with multidisciplinary teams across different time zones?

Remote Geospatial Data Scientists often work with professionals in fields like environmental science, urban planning, and software engineering, many of whom may be distributed globally. Effective collaboration relies on clear communication, regular virtual meetings, and the use of shared platforms for data, code, and project management. Flexible scheduling and asynchronous communication tools are key to coordinating across time zones, ensuring that all team members can contribute to project milestones efficiently. Building strong documentation and leveraging collaborative GIS and data platforms further help streamline workflows and maintain project momentum in a remote environment.

What are the key skills and qualifications needed to thrive as a Remote Geospatial Data Scientist, and why are they important?

To thrive as a Remote Geospatial Data Scientist, you need a strong background in spatial analysis, statistics, and programming, typically supported by a degree in geography, computer science, or a related field. Experience with GIS software (such as ArcGIS or QGIS), remote sensing tools, and programming languages like Python or R is essential, along with familiarity with cloud-based data platforms. Strong problem-solving, self-motivation, and effective communication skills are vital for collaborating remotely and turning complex geospatial data into actionable insights. These skills enable professionals to efficiently interpret and analyze spatial data, deliver valuable solutions, and work effectively within distributed teams.

What is a Remote Geospatial Data Scientist?

A Remote Geospatial Data Scientist is a professional who analyzes and interprets spatial data, such as maps, satellite imagery, and GPS data, to solve problems or provide insights, all while working from a location outside of a traditional office. They use statistical, mathematical, and programming skills to process large geospatial datasets and often collaborate with teams virtually. Their work can support a variety of industries, including environmental monitoring, urban planning, and logistics, by providing actionable geographic insights. Remote geospatial data scientists commonly use tools like GIS software, Python, and machine learning frameworks. Communication and collaboration tools are also essential for effective remote work.
What are the most commonly searched types of Geospatial Data Scientist jobs in California? The most popular types of Geospatial Data Scientist jobs in California are:
What job categories do people searching Remote Geospatial Data Scientist jobs in California look for? The top searched job categories for Remote Geospatial Data Scientist jobs in California are:
What cities in California are hiring for Remote Geospatial Data Scientist jobs? Cities in California with the most Remote Geospatial Data Scientist job openings:
Infographic showing various Remote Geospatial Data Scientist job openings in California as of July 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% Remote job distribution.
Real Estate Data Scientist - Remote

Real Estate Data Scientist - Remote

Harbor Freight Tools

Calabasas, CA โ€ข On-site, Remote

$98K - $147K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

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.ย 
  • 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.ย ย ย ย ย ย ย ย ย 
  • 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:ย  No
  • Decision making:ย 
    • Develops models and analytical frameworks used in strategic decision-making
  • Travel:ย  Up to 10%
  • Flex Designation:ย  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.