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Spatial Data Science Jobs (NOW HIRING)

CoStar Group

Land.com - Senior Data Scientist

Austin, TX · On-site

... spatial joins Preferred Qualifications: * Advanced degree in Economics, Data Science, Agricultural Economics, Statistics, Geospatial Science, Applied Mathematics, or Computer Science * Experience ...

Apple

Data Scientist

Cupertino, CA

$141K - $258K/yr

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 ...

TMS

Agentic Data Engineer

Richmond, VA · On-site

$80 - $95/hr

Collaborate with data scientists and engineers to preprocess data, train models, and integrate AI ... Experience with GIS spatial data to create markers on maps ( lat long nearest topology of road, geo ...

Staffingine LLC

Drone Data Engineer

Houston, TX · On-site

$109K - $131K/yr

Work closely with data science teams to operationalize AI models on drone data * Systems Cloud ... Knowledge of GIS tools spatial data formats and mapping systems * Cloud Systems * Experience with ...

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Leidos

Software Engineer/Data Science Librarian

Arnold, MO

$101K - $121K/yr

Leidos is seeking a Software Engineer / Data Science Librarian to manage and optimize databases ... Database Management & Spatial Content Generation * Manage and maintain databases supporting GEOINT ...

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Spatial Data Science information

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$44.5K

$129.7K

$177.5K

How much do spatial data science jobs pay per year?

As of Jul 1, 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 the highest paying GIS job?

The highest paying GIS jobs are often senior roles such as GIS Director, Geospatial Data Scientist, or GIS Manager, with salaries exceeding $100,000 annually. These positions typically require advanced skills in spatial analysis, programming, and leadership, and may involve working with tools like ArcGIS, Python, or SQL.

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.

Is GIS hard to get a job in?

Getting a job in GIS or spatial data science can be competitive, but having strong skills in GIS software like ArcGIS or QGIS, programming languages such as Python or R, and a solid understanding of spatial analysis can improve employability. Relevant certifications and a portfolio of projects also enhance job prospects in this field.

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.

Is 40 too late for data science?

Age is generally not a barrier to entering a data science or spatial data science career, as skills and experience are more important. Many professionals successfully transition into data science later in life by acquiring relevant skills such as programming, statistics, and data visualization, often through online courses or certifications. Employers value diverse experiences, and continuous learning can help you stay competitive regardless of age.

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.

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 growing use of spatial analysis, remote sensing, and GIS software like ArcGIS and QGIS contributes to strong job prospects and competitive salaries in this field.

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
Land.com - Senior Data Scientist

Land.com - Senior Data Scientist

CoStar Group

Austin, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 19 days ago

Job description

Land.com - Senior Data Scientist
Job Description
CoStar Group (NASDAQ: CSGP) is a leading global provider of commercial and residential real estate information, analytics, and online marketplaces. Included in the S&P 500 Index, CoStar Group is on a mission to digitize the world's real estate, empowering all people to discover properties, insights and connections that improve their businesses and lives.
We have been living and breathing the world of real estate information and online marketplaces for over 35 years, giving us the perspective to create truly unique and valuable offerings to our customers. We've continually refined, transformed and perfected our approach to our business, creating a language that has become standard in our industry, for our customers, and even our competitors. We continue that effort today and are always working to improve and drive innovation. This is how we deliver for our customers, our employees, and investors. By equipping the brightest minds with the best resources available, we provide an invaluable edge in real estate.
Land.com
Land.com offers the largest and most effective marketplaces to discover, buy and sell rural real estate. The Land.com network connects millions of active buyers and landowners with the best local real estate professionals every month across three platforms.
Learn more about Land.com.
Role Description:
We are seeking a Senior Data Scientist to lead development and expansion of AcreValue's predictive land valuation models and to help build the foundation for future AI-driven capabilities within the platform.
This role will focus primarily on expanding AV+ parcel-level land valuation and predictive modeling capabilities in collaboration with internal engineering and product teams.
The ideal candidate combines strong econometric and statistical modeling skills with geospatial data expertise, and can design models that are interpretable, defensible, and explainable to both technical and non-technical stakeholders. Equally important is the ability to independently research complex problems, investigate economic, geospatial, and environmental factors influencing land valuation, identify relevant datasets, evaluate modeling approaches, and translate findings into practical production models.
This role will work closely with engineering teams to operationalize valuation modeling workflows and scalable prediction processes, while contributing technical expertise toward the platform's future AI initiatives, including natural language parcel search and AI-driven land insights.
This role is located in our Austin office and has a schedule of 5 days on-site.
Responsibilities:
  • Design, develop, and maintain parcel-level land valuation and predictive models used across the AcreValue platform
  • Research and expand valuation methodologies across diverse geographies and land types using geospatial, economic, and environmental data
  • Develop statistical and econometric models that are transparent, defensible, and explainable to both technical and non-technical stakeholders
  • Research land-use, economic, environmental, and geospatial factors influencing land values and incorporate findings into production predictive modeling approaches
  • Identify and prototype new datasets and model features prior to engineering implementation
  • Define and implement model evaluation, validation, and monitoring frameworks
  • Partner with engineering teams to operationalize valuation modeling workflows models, including training, prediction generation, validation and retraining processes
  • Contribute to research, prototyping, and technical evaluation of AI-driven land intelligence capabilities

Basic Qualifications:
  • Bachelor's degree required from an accredited, not-for-profit, in-person college/university
  • A track record of commitment to prior employers.
  • Experience building statistical or econometric models in Python for real-world predictive applications
  • Experience working with large geospatial datasets and spatial data concepts, including vector and raster formats, coordinate systems, and spatial joins

Preferred Qualifications:
  • Advanced degree in Economics, Data Science, Agricultural Economics, Statistics, Geospatial Science, Applied Mathematics, or Computer Science
  • Experience with Python geospatial libraries such as GeoPandas, Shapely, GDAL, or Rasterio
  • Experience working with spatial databases such as PostGIS or MongoDB with geospatial queries
  • Experience with parcel data, land cover datasets, satellite imagery, or soil and cropland data layers
  • Background in agricultural economics, farmland valuation, or real estate valuation
  • Experience deploying data science or machine learning systems in cloud environments such as AWS
  • Familiarity with GIS tools such as QGIS

What's in it for you?
When you join CoStar Group, you'll experience a collaborative and innovative culture working alongside the best and brightest to empower our people and customers to succeed.
We offer you generous compensation and performance-based incentives. CoStar Group also invests in your professional and academic growth with internal training, and tuition reimbursement.
Our benefits package includes (but is not limited to):
  • Comprehensive healthcare coverage: Medical / Vision / Dental / Prescription Drug
  • Life, legal, and supplementary insurance
  • Virtual and in person mental health counseling services for individuals and family
  • Commuter and parking benefits
  • 401(K) retirement plan with matching contributions
  • Employee stock purchase plan
  • Paid time off
  • Tuition reimbursement
  • On-site fitness center and/or reimbursed fitness center membership costs (location dependent), with yoga studio, Pelotons, personal training, group exercise classes
  • Access to CoStar Group's Employee Resource Groups
  • Complimentary gourmet coffee, tea, hot chocolate, fresh fruit, and other healthy snacks

We welcome all qualified candidates who are currently eligible to work full-time in the United States to apply. However, please note that CoStar Group is not able to provide visa sponsorship for this position.
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#Land.com
CoStar Group is an Equal Employment Opportunity Employer; we maintain a drug-free workplace and perform pre-employment substance abuse testing

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