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Spatial Data Science Jobs (NOW HIRING)

GeoYeti

Senior Geospatial Data Scientist

Reston, VA

Our Insight Solutions division delivers intelligence analysis, advanced data science, and strategic ... Expert level understanding of spatial data storage formats such as ESRI GeoDatabases, shapefiles ...

GeoYeti

Senior Geospatial Data Scientist

Reston, VA · On-site

Our Insight Solutions division delivers intelligence analysis, advanced data science, and strategic ... Expert level understanding of spatial data storage formats such as ESRI GeoDatabases, shapefiles ...

Esri

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 ...

Spatial Data Logic

GIS Coordinator

Ensure spatial data model integrity: enforce consistent schemas, metadata standards, coordinate ... Science, or related field - preferred * Hands-on experience working with GIS platforms (e.g. ArcGIS ...

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Spatial Data Science information

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How much do spatial data science jobs pay per year?

As of Jun 10, 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 June 2026, with employment types broken down into 2% As Needed, 74% Full Time, and 24% Part Time. Highlights an 73% Physical, 1% Hybrid, and 26% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Senior Geospatial Data Scientist

GeoYeti

Reston, VA

Full-time

Posted 10 days ago

Job description

Overview

At Bcore, our strength comes from how we deliver impact to the mission. Whether it's architecting critical IT solutions, producing actionable intelligence, or developing cutting edge technology, we succeed because of the expertise, collaboration, and agility of our teams. Our Insight Solutions division delivers intelligence analysis, advanced data science, and strategic decision support. Bcore accelerates decisive advantage for warfighters and intelligence professionals by fusing human insight, rapid-fire engineering, precision-measured outcomes, and relentless grit into mission-ready solutions. 

Are you ready to lean into analytic approaches that show customers the power of both technical and methodological innovation? Join our growing team supporting customer missions as a Senior Geospatial Data Scientist in Reston, VA and remote.

Responsibilities
  • Identify corollary datasets to compare against model outputs, especially those with which were unlikely used as part of the training set.
  • Assist in the evaluation of the effectiveness of ML models.
Qualifications

Required Qualifications:   

  • Active TS/SCI clearance with CI poly required to start
  • Expert level understanding of Python, including geospatial libraries like Fiona and Shapely.
  • Expert level understanding of spatial data storage formats such as ESRI GeoDatabases, shapefiles, GeoPackage, and text-based storage in spatial databases such as PostGIS.
  • Ideally an understanding of storage formats and methodologies for ML models.
What you can expect from us

BCore is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation or any other characteristic protected by law.

Employment Type: FULL_TIME

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