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Spatial Data Science Jobs in Tennessee (NOW HIRING)

Skilled at teaching geographic model application, spatial data analysis, and free-response question ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Skilled at teaching geographic model application, spatial data analysis, and free-response question ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Skilled at teaching geographic model application, spatial data analysis, and free-response question ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Skilled at teaching geographic model application, spatial data analysis, and free-response question ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Skilled at teaching geographic model application, spatial data analysis, and free-response question ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Skilled at teaching geographic model application, spatial data analysis, and free-response question ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

... spatial analysis. An employee in this position will collaborate with Tennessee State Parks ... Science, Data Science, or a related field and 2 years of relevant work experience is required.

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Spatial Data Science information

See Tennessee salary details

$40.4K

$117.7K

$161.1K

How much do spatial data science jobs pay per year?

As of Jun 10, 2026, the average yearly pay for spatial data science in Tennessee is $117,733.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,900.00 and $124,800.00 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 Tennessee? For Spatial Data Science jobs in Tennessee, the most frequently searched job titles are:
What cities in Tennessee are hiring for Spatial Data Science jobs? Cities in Tennessee with the most Spatial Data Science job openings:
Infographic showing various Spatial Data Science job openings in Tennessee as of June 2026, with employment types broken down into 2% As Needed, 75% Full Time, and 23% Part Time. Highlights an 73% Physical, 1% Hybrid, and 26% Remote job distribution, with an average salary of $117,733 per year, or $56.6 per hour.
Geospatial Data Engineer

Geospatial Data Engineer

Oak Ridge National Laboratory

Oak Ridge, TN • On-site

$99K - $119K/yr

Full-time

Posted 18 days ago


Oak Ridge National Laboratory rating

9.3

Company rating: 9.3 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

4th of 103 rated laboratories


Job description

Job Summary:
Oak Ridge National Laboratory (ORNL) is a U.S. Department of Energy national laboratory focused on solving complex scientific challenges. The Geospatial Data Engineer will support research and operational workflows in geospatial data science, applied machine learning, and engineering practices to deliver geospatial products for national security and humanitarian efforts.
Responsibilities:
• Develop, maintain, and operationalize geospatial data science pipelines across ingestion, feature engineering, training, inference, evaluation, and delivery, using reproducible MLOps practices (version control, testing, experiment tracking, containerization, and CI/CD).
• Support implementation of agentic AI workflows to discover, gather, and prepare data from open-source repositories (e.g., catalogs, APIs, and bulk downloads), including provenance tracking, metadata extraction, and licensing/usage notes.
• Build scalable geospatial data preparation and validation routines for raster and vector data (projection harmonization, spatial joins, tiling/chunking, and QA/QC).
• Develop geospatial validation frameworks for model outputs (e.g., comparisons to reference datasets, spatial cross-validation, summary dashboards, and automated report generation).
• Support documentation, metadata development, and version tracking for data products and model releases; contribute to technical summaries, figures, and reports/publications as appropriate.
• Participate in code reviews, model reviews, and data readiness reviews to ensure analytical defensibility, transparency, and fitness-for-use in operational and decision-support contexts.
• Collaborate with research staff to integrate new data sources, indicators, and modeling approaches into existing workflows; communicate clearly across technical and domain teams.
Qualifications:
Required:
• Bachelor’s degree and 3+ year’s experience in Geography, GIScience, Computer Science, Data Science, Statistics, Engineering, or a related field with a strong quantitative and software development emphasis.
• Demonstrated experience with geospatial analysis using Python in a production or research to production environment leveraging common geospatial libraries (e.g., geopandas, rasterio, shapely, pyproj) and/or enterprise GIS tooling (e.g., PostGIS).
• Strong software engineering fundamentals: Git-based workflows, testing, code review, and writing maintainable, well-documented code.
• Experience preparing and validating raster and vector datasets (data cleaning, transformation, projection/CRS management, and quality control).
• Working knowledge of machine learning and statistical modeling concepts (e.g., regression, classification, clustering, model evaluation).
• Ability to work effectively in a team-based, production-oriented research environment and communicate technical results to diverse stakeholders.
Preferred:
• Master’s degree in a relevant discipline or equivalent applied experience in geospatial data science, MLOps, or applied machine learning.
• Experience with modern MLOps tooling and practices (e.g., MLflow or equivalent experiment tracking, model registries, containerization, reproducible environments).
• Experience building data pipelines and workflow orchestration (e.g., Airflow, Prefect, Dagster, Make/Snakemake) and working in Linux/HPC environments.
• Experience with large, multi-resolution geospatial datasets and performance-oriented processing (tiling, chunking, parallelization; Dask/Spark a plus).
• Experience using or building agentic/LLM-enabled workflows for data discovery, extraction, and normalization, with attention to provenance, reproducibility, and quality.
• Familiarity with uncertainty, data limitations, and bias in population and demographic modeling and in applied geospatial decision-support contexts.
• Active or eligible U.S. security clearance or ability to obtain one.
Company:
Oak Ridge National Laboratory holds a range of R&D assignments, from fundamental nuclear physics to applied R&D on advanced energy systems. Founded in 1943, the company is headquartered in Oak Ridge, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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