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Geospatial Data Scientist Jobs (NOW HIRING)

Data Scientist Prin

Augusta, GA · On-site

$107K - $182K/yr

The Geospatial Data Scientist will be expected to lead efforts such as, but not limited to: * design, implementation, and operate data driven approaches to client's intelligence requirements ...

Process and analyze large-scale geospatial datasets * Create data visualization and reporting ... Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field * 5+ ...

Process and analyze large-scale geospatial datasets * Create data visualization and reporting ... Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field * 5+ ...

Process and analyze large-scale geospatial datasets * Create data visualization and reporting ... Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field * 5+ ...

Senior Geospatial Data Engineer

Mclean, VA · On-site

$116K - $139K/yr

... Science, Data Science, Engineering, or a related technical discipline. • 12+ years of ... geospatial technology, software development, data engineering, data analysis, or a related ...

The Senior Data Scientist - Geospatial serves as a technical leader responsible for designing and delivering advanced analytical and modeling solutions using geospatial data. This role leads complex ...

Collaborate with geospatial data analysts to understand and automate workflows and improve human ... Support scientific research projects and develop geospatial algorithms while collaborating among ...

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Geospatial Data Scientist information

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$37.5K

$122.7K

$196.5K

How much do geospatial data scientist jobs pay per year?

As of Aug 22, 2026, the average yearly pay for geospatial data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a geospatial data scientist?

A Geospatial Data Scientist analyzes spatial and geographic data to extract insights, create predictive models, and support decision-making. They use tools like GIS, remote sensing, machine learning, and statistical analysis to process location-based data. Their work spans various industries, including urban planning, environmental monitoring, agriculture, and logistics. By leveraging spatial data, they help optimize operations, manage resources, and solve complex geographic problems.

What does a geospatial data scientist do?

As a Geospatial Data Scientist, your daily tasks often involve collecting, cleaning, and analyzing spatial datasets using GIS tools and programming languages. You may be responsible for developing spatial models, visualizing geographic data through interactive maps, and generating reports to help guide strategic decisions. Collaboration with professionals from engineering, urban planning, or environmental science teams is common, requiring you to communicate complex analyses in a clear and actionable manner. Additionally, you might participate in project meetings to align your work with organizational goals and stakeholder needs. This dynamic role blends technical analysis with communication and teamwork, making each day varied and intellectually stimulating.

What are the key skills and qualifications needed to thrive as a geospatial data scientist?

Geospatial Data Scientists require expertise in spatial analysis, statistics, and data modeling, typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), programming languages like Python or R, and familiarity with spatial databases are often expected, while certifications in GIS can be advantageous. Strong problem-solving abilities, collaboration, and effective communication skills help professionals translate complex data into actionable insights and work well with diverse teams. Mastery of these skills ensures accurate geospatial analyses and supports informed, data-driven decision making in various industries.

How much does a geospatial data scientist make?

A geospatial data scientist's salary typically ranges from $70,000 to $130,000 annually, depending on experience, education, location, and industry. Senior roles or those with specialized skills in GIS tools and programming may earn higher compensation.

Is geospatial data scientist still in demand?

Yes, geospatial data scientists are in high demand due to the increasing use of geographic information systems (GIS), remote sensing, and spatial analysis across industries such as urban planning, environmental management, and transportation. The role often requires skills in programming, data analysis, and tools like Python, R, and GIS software, with strong job growth projected in the coming years.
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What cities are hiring for Geospatial Data Scientist jobs?

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What are the most commonly searched types of Geospatial Data Scientist jobs?

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What states have the most Geospatial Data Scientist jobs?

States with the most job openings for Geospatial Data Scientist jobs include:

Infographic showing various Geospatial Data Scientist job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $122,738 per year, or $59 per hour.

Sr. Data Scientist

Delan Associates, Inc.

Juno Beach, FL • On-site

Contractor

Posted 12 days ago


Job description


The Senior Data Scientist - Geospatial serves as a technical leader responsible for designing and delivering advanced analytical and modeling solutions using geospatial data. This role leads complex spatial analytics efforts, mentors less-experienced data scientists, and collaborates with GIS teams and business leaders to translate geospatial data into actionable insights. The position requires deep expertise in data science techniques and hands-on experience with spatial analytics at scale
Responsibilities:
  • This position leads the design and development of scalable GIS tools, analytical applications, spatial data products, and reusable geoprocessing capabilities that support complex business and operational needs.
  • Responsibilities include establishing technical standards and development frameworks; guiding the architecture of enterprise geospatial solutions; developing and overseeing spatial data pipelines, APIs, and automation workflows; and integrating GIS capabilities with cloud platforms, enterprise data systems, and AI services.
  • Candidates should hold an advanced degree, with at least 6-8 years of experience in data science and a preference for data science in GIS during the last 4 years.
  • Extensive experience developing production-grade analytical tools and applications, and a strong track record of delivering enterprise-level business impact.
  • Preferred qualifications include significant experience developing GIS tools and applications using Esri technologies such as ArcGIS Pro, ArcGIS Enterprise, ArcGIS Online, ArcPy, the ArcGIS API for Python, ArcGIS REST APIs, and ArcGIS Maps SDKs.

Experience developing custom geoprocessing tools, Python toolboxes, web-based mapping applications, dashboards, widgets, extensions, and automated spatial analysis workflows is highly valued.