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Spatial Data Science Jobs (NOW HIRING)

Leidos

Software Engineer/Data Science Librarian

Arnold, MO · On-site

$101K - $121K/yr

Leidos is seeking a Software Engineer / Data Science Librarian to manage and optimize databases ... Database Management & Spatial Content Generation * Manage and maintain databases supporting GEOINT ...

Electrosoft

Data Architect

Arlington, VA · On-site +1

$73.25 - $94.25/hr

Design and maintain enterprise data architectures that support geospatial operations, spatial ... Master's degree in Computer Science, Information Systems, Data Science, Geospatial Science ...

Axle

Data Scientist II

Rockville, MD

With experts in biomedical science, software engineering, and program management, we focus on ... Support figure generation for QC, differential expression, pathway, and spatial analyses.

Axle

Data Scientist II

Rockville, MD · On-site

With experts in biomedical science, software engineering, and program management, we focus on ... Support figure generation for QC, differential expression, pathway, and spatial analyses.

Esri

Data Scientist I

Saint Louis, MO · On-site

$70K - $110K/yr

We're seeking a Data Scientist who combines technical expertise with strong interpersonal skills to ... science, physics, or a STEM related field Recommended Qualifications * Experience with spatial and ...

Google

Product Data Scientist, Geo

Mountain View, CA · On-site

Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a ... spatial data, and the relative impact of manual versus automated edits. Individual pay is ...

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How much do spatial data science jobs pay per year?

As of Aug 11, 2026, the average yearly pay for spatial data science in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is spatial data science?

Spatial data science is a field that combines data science techniques with geographic information systems (GIS) to analyze and interpret spatial or location-based data. It involves collecting, processing, and visualizing data that has a geographic or spatial component, such as maps, satellite images, or GPS coordinates. Spatial data scientists use methods from statistics, machine learning, and computer science to solve problems related to urban planning, environmental monitoring, transportation, and more. The insights gained from spatial data science help organizations make better decisions based on the relationships and patterns found in geographic data.

What are the key skills and qualifications needed to thrive as a spatial data scientist, and why are they important?

To thrive as a Spatial Data Scientist, you need a strong background in statistics, geospatial analysis, and programming (often with Python or R), typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), spatial databases (like PostGIS), and relevant certifications (e.g., Esri Technical Certification) is commonly required. Strong analytical thinking, problem-solving abilities, and effective communication are vital soft skills to interpret spatial data and convey insights to stakeholders. These competencies are crucial for extracting actionable insights from complex geospatial datasets and supporting informed decision-making.

What is the difference between Spatial Data Science vs Geospatial Analyst?

AspectSpatial Data ScienceGeospatial Analyst
Required CredentialsDegree in GIS, Geography, Data Science, or related fields; often includes certifications in GIS or data analysisDegree in Geography, GIS, or related fields; certifications in GIS software are common
Work EnvironmentData analysis, modeling, and programming; often in tech or research settingsMapping, data visualization, and GIS software use; typically in government, environmental, or urban planning agencies
Employer & Industry UsageTech companies, research institutions, urban planning, environmental agenciesGovernment agencies, environmental consultancies, urban planning firms

Spatial Data Science focuses on analyzing spatial data using advanced data science techniques, programming, and modeling. In contrast, Geospatial Analysts primarily work with GIS software to create maps and visualize spatial data. While both roles require GIS knowledge, Spatial Data Scientists often have stronger programming and statistical skills, working on complex data analysis projects, whereas Geospatial Analysts focus more on mapping and data visualization tasks.

What are some typical challenges spatial data scientists face when integrating geospatial data from multiple sources?

Spatial data scientists often encounter challenges like inconsistencies in data formats, varying coordinate reference systems, and differences in spatial resolution when integrating geospatial data from multiple sources. Addressing these requires familiarity with data transformation tools and a strong understanding of spatial data standards. Additionally, ensuring data quality and managing large datasets can be complex, so attention to detail and effective use of GIS software are crucial for successful integration.
More about Spatial Data Science jobs
What cities are hiring for Spatial Data Science jobs? Cities with the most Spatial Data Science job openings:
What states have the most Spatial Data Science jobs? States with the most job openings for Spatial Data Science jobs include:
What job categories do people searching Spatial Data Science jobs look for? The top searched job categories for Spatial Data Science jobs are:
Spatial Data Science jobs near you
Infographic showing various Spatial Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Location Analytics Developer - Lakeland

Publix Super Markets, Inc.

Lakeland, FL • On-site

Full-time

Re-posted 2 days ago

Publix rating

6.8

Company rating: 6.8 out of 10

Based on 4,667 frontline employees who took The Breakroom Quiz

28th of 122 rated grocery stores

Job description

The purpose of this position is to provide location specific recommendations, whether at the store, market or customer level, in support of Real Estate, Operations, Marketing, BAR, Emerging Business, Loss Prevention, Human Resources, alternative business concepts, IS/TS, and merchandising initiatives with a focus on automation and self-service for our business partners. This allows the team to continue to take on additional workload with a small head-count.
Example: Optimize store layouts, merchandising changes based on shifting demographics surrounding our stores, assisting with site selection for new stores, developing applications/programs/processes with a focus on automation for the business partner.
The impact this position has on Publix is directly related to the success of our stores/initiatives. Location is extremely important in success.
Responsibilities include:
  • Analysis & Report Automation: Maintain/develop a self-serve environment that allows department-specific users to exploit Spatial Data Science & GIS' expertise using developed applications that provide data-backed solutions to the asked business question(s).
  • Research, summarize, analyze, synthesize, and visualize multiple datasets from internal sources (BAR, IS, RE, CRM, MBA, CI, LP...etc.) and external sources (competition, sales, demographics, purchase behaviors, customer data...etc.) into a comprehensive final deliverable (report, presentation, infographic, map, story-map...etc.) that enables decision makers to quickly advance our business backed by data driven decision-making.
  • Support the innovation and enable the Spatial Data Science & GIS Team to maintain a high level of awareness of location-based data, systems, processes.
  • Manage existing contracts and renewals to ensure Publix is not in breach of contract, and there is no lapse in data/service providers
  • Train GIS Analysts on Location Analytics and the skillsets needed to progress into a Location Analytics Developer (spatial statistics, Alteryx, existing methodologies/processes...etc.)
  • Dedicating time to Marketing innovation and quality improvement.
  • managing special Marketing related assignments, which can include but is not limited to: project management, executing reporting and presenting results to executive leadership.

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