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Spatial Data Science Jobs in Seattle, WA (NOW HIRING)

McMillen, Inc.

GIS Specialist

Kirkland, WA · On-site

$50K - $95K/yr

In this role, you'll support scientific and engineering initiatives through cartography, geospatial analysis, data visualization, and spatial data management. Initially, your primary focus will be ...

McMillen, Inc.

GIS Specialist

Kirkland, WA

$50K - $95K/yr

In this role, you'll support scientific and engineering initiatives through cartography, geospatial analysis, data visualization, and spatial data management. Initially, your primary focus will be ...

Amazon

Applied Science Manager, Prime Air

Seattle, WA

Our team of scientists, engineers, and aerospace professionals is solving these exact problems. We ... Strong foundation in Geospatial Information Systems (GIS) and spatial data analysis. Proven track ...

Amazon

Applied Science Manager, Prime Air

Seattle, WA · On-site

Our team of scientists, engineers, and aerospace professionals is solving these exact problems. We ... Strong foundation in Geospatial Information Systems (GIS) and spatial data analysis. Proven track ...

Amazon

Applied Science Manager, Prime Air

Seattle, WA · On-site

Our team of scientists, engineers, and aerospace professionals is solving these exact problems. We ... Strong foundation in Geospatial Information Systems (GIS) and spatial data analysis. Proven track ...

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Showing results 21-40

All JobsSpatial Data Science JobsSpatial Data Science Jobs in Seattle, WA

Spatial Data Science information

See Seattle, WA salary details

$50.6K

$147.6K

$202K

How much do spatial data science jobs pay per year?

As of Aug 18, 2026, the average yearly pay for spatial data science in Seattle, WA is $147,621.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,300.00 and $156,500.00 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 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 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 does a spatial data scientist do?

A spatial data scientist analyzes geographic data to identify patterns, relationships, and trends using tools like GIS software and programming languages such as Python or R. They develop models, visualize spatial information, and support decision-making in fields like urban planning, environmental management, and logistics.

What are popular job titles related to Spatial Data Science jobs in Seattle, WA?

For Spatial Data Science jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Spatial Data Science jobs in Seattle, WA look for?

The top searched job categories for Spatial Data Science jobs in Seattle, WA are:

Spatial Data Science jobs near you
Infographic showing various Spatial Data Science job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $147,621 per year, or $71 per hour.

Quantitative Analysis Data Science Support

Think Tank, Inc.

Seattle, WA • On-site

Other

Re-posted 10 days ago

Job description

*Position is Subject to Contract Award POSITION DESCRIPTION:Description of Duties:Analyze spatial and temporal variability in abundance and composition of fish, their prey, competitors, predators, and habitats.Analyze and generate relationships between fish responses (e.g., density, bio...

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