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Spatial Data Science Jobs in Washington (NOW HIRING)

Vantor

Senior Geospatial Data Engineer

Mclean, VA · On-site

$116K - $139K/yr

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators ... Science, Data Science, Engineering, or a related technical discipline. • 12+ years of ...

GeoSearch

Geospatial Analyst III

Fairfax, VA

$77K - $99K/yr

In this role, you'll work hands-on with spatial data, analysis, and technology to solve complex ... Bachelor's degree in computer science, data science, GIS or other relevant geospatial or data ...

THOMSON REUTERS

Data Scientist

Mclean, VA · Hybrid

Bachelor's or Master'sDegree in a technical field (e.g., data science, statistics, computer science ... Large Data Analysis: statistical methods, graph networks, anomaly detection, spatial analysis ...

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All JobsSpatial Data Science JobsSpatial Data Science Jobs in Washington

Spatial Data Science information

See Washington salary details

$50.4K

$146.9K

$201K

How much do spatial data science jobs pay per year?

As of Aug 8, 2026, the average yearly pay for spatial data science in Washington is $146,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,700.00 and $155,700.00 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.
What are popular job titles related to Spatial Data Science jobs in Washington? For Spatial Data Science jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Spatial Data Science jobs in Washington look for? The top searched job categories for Spatial Data Science jobs in Washington are:
What cities in Washington are hiring for Spatial Data Science jobs? Cities in Washington with the most Spatial Data Science job openings:
Spatial Data Science jobs near you
Infographic showing various Spatial Data Science job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $146,916 per year, or $70.6 per hour.

Mid-Level Data Scientist with TS/SCI Clearance

CALNET Inc.

Springfield, VA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 14 days ago

Job description

Description
Founded in 1989, CALNET, Inc. has become one of the fastest growing privately held companies in the Technology, Intelligence Analysis, and Language Services consulting arena. Headquartered in Reston, VA, CALNET employees deliver true value to our customers by employing best practices, world-class technologies industry expertise in every project. CALNET is ISO 9001, ISO 20000, ISO 27001, CMMI-Level III for Services, and CMMC Level 2 certified.
We are currently searching for a talented, professional Mid-Level Data Scientistwith TS/SCI clearance to join our team to support NGA.
About the Job
The Senior Analytical Methodologist possesses skills that focus on GEOINT data enrichment and management. Applies expertise to exploit GEOINT data or information in order to develop advanced analytic processes, apply scientific approaches to test geospatial data for accuracy and precision, create automated services that support GEOINT creation and delivery, and/or structure and manage data for further use.
Requirements
  • 7 + years of demonstrated experience using quantitative and qualitative techniques to solve complex problems using analytic tools and techniques to solve complex problems such as GIS, quantitative methods and data visualization, modeling, systems analysis, comparative analysis and database development.
  • Bachelor's degree or master's degree in computer science or information technology discipline.
  • Demonstrated knowledge and experience in data mining, cleansing and exploring spatial, temporal and non-spatial data in both structured and unstructured formats.
  • Demonstrated knowledge of programming languages (e.g. Python, Java, JavaScript, SQL), modeling software, spatial analysis tools and concepts, data mining methods, database structures and analytic information extraction and visualization.
  • Current, active TS/SCI with the ability to obtain a CI Poly.

This opportunity is located in Springfield, VA. To apply, go to https://jobs.jobvite.com/calnet.
CALNET, Inc. offers a competitive base salary and a generous benefits package. This package includes medical, dental, vision, life, short- and long-term disability insurances, a 401(k)-retirement savings plan, and generous leave time.
CALNET, Inc. is an Equal Opportunity Employer; all qualified applicants are encouraged to apply. www.calnet.com
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