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Spatial Data Science Jobs (NOW HIRING)

WaterSuite

Spatial Data Manager

Braintree, MA

Spatial Data Manager performs a key role in the operations of WaterSuite by owning and maintaining ... Degree in computer science, geography, environmental science or relevant field * GISP, PMP or other ...

WaterSuite

Spatial Data Manager

Braintree, MA · On-site

Spatial Data Manager performs a key role in the operations of WaterSuite by owning and maintaining ... Degree in computer science, geography, environmental science or relevant field * GISP, PMP or other ...

The Nature Conservancy

CET Spatial & Data Analyst

Working closely with the Social Ecological Scientist, the analyst will contribute to data synthesis ... Conduct spatial analysis, mapping, and data visualization using GIS tools (e.g., QGIS, ArcGIS) to ...

Diamondback Energy

Data Science Geologist

Midland, TX · On-site

Diamondback Energy is seeking a Data Science Geologist to bridge traditional earth sciences with ... Leverage GIS and subsurface mapping tools to perform complex spatial analysis and create ...

Prescient Edge

Senior Data Scientist

Herndon, VA · On-site

Write either R or Python scripts to drive data science work: flows, have experience using SQL, and ... Possess prior experience with large data. spatial data, Multi-INT analytics, ML, and automated ...

Diamondback Energy

Data Science Geologist

Midland, TX · On-site

This Data Science Geologist will bridge traditional earth sciences with advanced data science and ... Spatial Analysis: Leverage GIS and subsurface mapping tools to perform complex spatial analysis and ...

Diamondbackenergy

Data Science Geologist

Midland, TX

This Data Science Geologist will bridge traditional earth sciences with advanced data science and ... Spatial Analysis: Leverage GIS and subsurface mapping tools to perform complex spatial analysis and ...

Apple

Data Scientist

Cupertino, CA · On-site

As Data Science organization, our goal is to harness the power of user data to help Maps make great ... spatial data analysis Prior proven industry experience with large data sets using technologies like ...

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 ...

Analytic Services Inc

Data Scientist

Washington, DC · On-site

You will leverage data science, machine learning, and statistical techniques to analyze, model, and ... for large, spatial, and multi-INT datasets. * Create and operate in distributed analytic ...

Analytic Services Inc

Data Scientist

Washington, DC · On-site

You will leverage data science, machine learning, and statistical techniques to analyze, model, and ... for large, spatial, and multi-INT datasets. * Create and operate in distributed analytic ...

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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.
Spatial Data Manager

Spatial Data Manager

WaterSuite

Braintree, MA

Full-time

Posted 9 days ago

Job description

Company Description

WaterSuite is a cloud based geospatial platform housing a large and growing inventory of spatial data layers of all types and sizes from numerous sources. WaterSuite is a unique and valuable resource for the drinking water community, supporting source water protection and online monitoring efforts, and is in use by many clients, including drinking water utilities, municipalities and states.

Job Description

Spatial Data Manager performs a key role in the operations of WaterSuite by owning and maintaining the spatial data model, overseeing and executing spatial data processes as well as working with other team members to evolve the data model and processes to address emerging needs.

Responsibilities:

  • Owns the spatial data model (conceptual level down to attribute level) and ensures compliance
  • Owns the spatial data processes and ensures timely and orderly execution
  • Spatial data processes include periodic layer updates with change tracking for hundreds of layers
  • Keeps documentation on spatial data model and processes current
  • Curates newly requested spatial data layers
  • Works with team members to extend or modify the spatial data model
  • Works with team members to build new processes or improve existing ones
  • Advises application development team on spatial functionality
  • Responds to ad-hoc spatial data or analysis requests
  • Trains other team members on spatial data model and processes as needed
  • Participates in agile teams, collects/reviews user stories, extracts requirements, creates/curates tickets
  • Prepare/participate/present in company events, workshops, conferences or other venues
Qualifications

Required Skills/Experience:

  • Keen attention to detail
  • Experience working with spatial data at scale
  • Experience working with large databases
  • Experience with PostgreSQL, PostGIS, SQL
  • Understanding of GIS and spatial concepts, tools, processes
  • Understanding of basic relational database concepts
  • Able to handle multiple tasks in a fast-paced environment
  • Excellent verbal, written, and interpersonal communication skills
  • Collaborative problem solver
  • Critical thinking to evaluate alternative solutions

Preferred Skills:

  • Familiarity with drinking water concepts, hydrology, watershed science or similar
  • Degree in computer science, geography, environmental science or relevant field
  • GISP, PMP or other relevant certification
  • Programming skills in python, R, JavaScript or similar
Additional Information

Location: Remote initially then Braintree, MA (at exit 6 off Route 93)

All your information will be kept confidential according to EEO guidelines.

Keywords: PostgreSQL, Postgres, PostGIS, PG Admin, SQL, QGIS, ESRI ArcGIS, geospatial analysis and visualization, geography, cartography, hydrology, map making, emergency response, hazard/risk analysis, watershed, JIRA, Atlassian Confluence, Slack, OpenLayers, python, jupyter notebooks, Azure Data Studio, R, JavaScript, TypeScript, ETL, ogr2ogr, GDAL, Cassandra, Docker, Vue.js, REST API, Tableau, Google Sheets, Excel, Amazon AWS

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