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Spatial Data Science Jobs in Tennessee (NOW HIRING)

Deep knowledge of physical geography, human geography, map reading and spatial analysis, climate ... Guides students through reading topographic and thematic maps, analyzing population data and ...

Deep knowledge of physical geography, human geography, map reading and spatial analysis, climate ... Guides students through reading topographic and thematic maps, analyzing population data and ...

Deep knowledge of physical geography, human geography, map reading and spatial analysis, climate ... Guides students through reading topographic and thematic maps, analyzing population data and ...

Deep knowledge of physical geography, human geography, map reading and spatial analysis, climate ... Guides students through reading topographic and thematic maps, analyzing population data and ...

Data capturing and conversion of GIS data for all GIS activities Perform complex GIS analyses with ... MINIMUM QUALIFICATIONS Bachelor's Degree in GIS, Geography, Engineering, Computer Science, Planning ...

Operator (Melt) 1st shift

Chattanooga, TN · On-site

$16.25 - $21.50/hr

... material science innovator. More than 50 years of experience in medical, aerospace, energy ... The ability to communicate clearly is imperative, as is the ability to manipulate data using ...

Operator (Melt) 1st shift

Chattanooga, TN · On-site

$16.25 - $21.50/hr

... material science innovator. More than 50 years of experience in medical, aerospace, energy ... The ability to communicate clearly is imperative, as is the ability to manipulate data using ...

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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 Jul 22, 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 GIS jobs pay the most?

Senior GIS analyst, GIS manager, and geospatial data scientist roles tend to offer the highest salaries in the GIS field, often exceeding $80,000 to $100,000 annually depending on experience, location, and industry. These positions typically require advanced skills in GIS software, programming, and data analysis, with certifications like GISP enhancing earning potential.

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.

Can data scientists make $300k?

Data scientists, including those specializing in spatial data science, can earn $300,000 or more at senior levels or in high-demand industries, especially with extensive experience, advanced skills in machine learning, and proficiency in tools like Python or R. Achieving this salary often requires working in large companies, consulting roles, or locations with high living costs, and may involve additional responsibilities or leadership positions.

What does a spatial data scientist do?

A spatial data scientist analyzes geographic data to identify patterns, trends, and relationships 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, or logistics.

Is GIS a high demand job?

GIS (Geographic Information Systems) professionals, including those in spatial data science, are in high demand across industries such as urban planning, environmental management, and transportation. The increasing use of spatial analysis, remote sensing, and GIS tools like ArcGIS and QGIS contributes to strong job growth and opportunities for skilled workers.

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 job categories do people searching Spatial Data Science jobs in Tennessee look for? The top searched job categories for Spatial Data Science jobs in Tennessee are:
Infographic showing various Spatial Data Science job openings in Tennessee as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $117,733 per year, or $56.6 per hour.
Faculty Position - Department of Computational Biology

Faculty Position - Department of Computational Biology

St. Jude Children's Research Hospital

Memphis, TN • On-site

Full-time

Posted 16 days ago


St. Jude Children's Research Hospital rating

8.6

Company rating: 8.6 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

37th of 1,022 rated hospitals


Job description

SJCRH
Be the force behind the cures. From analyzing complex biomedical data in pediatric cancer to creating innovative technologies and computational tools, your work at St. Jude can directly impact patient care.
The Department of Computational Biology invites applications for Assistant/Associate/Full Member (faculty) positions in, but not limited to, the following areas:
A - Omics Technologies
We seek a computational technology innovator to develop next generation omics platforms for pediatric biology and diseases. Areas of interest include RNA biology (splicing/fusions), CRISPR functional genomics (CRISPRi/a, Perturb seq, combinatorial screens), single cell and spatial omics, metabolomics, and immunopeptidomics. The successful candidate will pioneer assay-algorithm co design, demonstrate cross disciplinary leadership and lead reproducible & open science
B - AI in Biomedicine
We seek an AI-first scientist to build foundation models and agentic AI tools spanning DNA/RNA/protein/imaging/spatial/EHR data for pediatric precision medicine. Topics include regulatory genomics foundation models, multimodal tissue/cell models (WSI + spatial + single-cell), proteogenomic/neoantigen prediction, computational pathology (WSI modeling, slide-omics fusion) and clinical informatics, plus trustworthy AI (calibration, uncertainty, drift monitoring). Candidates should have a record of impactful methods/tools, experience with clinical informatics pipelines, and a commitment to safe, reproducible, clinic-ready AI. Experience building LLM-driven, agentic systems for automated analysis or experiment planning with appropriate guardrails is highly valued.
Environment & Resources
The Department occupies 28,700 square feet of laboratory and office space. Investigators have dedicated shared resources for large-scale data analysis and functional validation, including priority access to cloud computing, a local high-performance computing facility housed in a state-of-the-art data center, a genomics laboratory for developing new omics technologies and assays, a wet lab supporting dry-lab faculty, and an software engineering team for high-throughput analysis and pipeline automation. The Department is key in multiple completed and ongoing institutional projects, including Pediatric Cancer Genome Project (PCGP), St. Jude Cloud, PedDep Accelerator, Real Time Clinical Genomics, iTARGETS, and COMET. The research environment at St. Jude is highly collaborative, with opportunities across basic and clinical departments and access to institution-wide core facilities led by PhD-level scientists.
Compensation & Appointment
We offer highly competitive packages, including generous startup funds, computing resources, equipment, laboratory space, personnel support, and potential institutional support beyond the start-up phase.
Appointments at the Assistant or Associate or Full Member level will be considered.
Qualifications
  • PhD (or equivalent) with at least three years of relevant postgraduate experience, or a demonstrated track record of developing novel, high-impact computational methods.
  • For Area A: evidence of assay-algorithm co-design in RNA/CRISPR/single-cell/spatial/metabolomics.
  • For Area B: experience with foundation models, multimodal learning, clinical NLP, and trustworthy AI; familiarity with clinical informatics.

How to Apply
Please submit the following directly via the online application:
(1) a curriculum vitae, (2) a 2-3 page summary of research interests, and (3) the names of three references
For more information, contact ComputationalBiologyRecruitment@stjude.org.
St. Jude is an Equal Opportunity Employer
No Search Firms
St. Jude Children's Research Hospital does not accept unsolicited assistance from search firms for employment opportunities. Please do not call or email. All resumes submitted by search firms to any employee or other representative at St. Jude via email, the internet or in any form and/or method without a valid written search agreement in place and approved by HR will result in no fee being paid in the event the candidate is hired by St. Jude.

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