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Spatial Data Science Jobs in New Mexico (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 ...

Environmental Field Technician

Carlsbad, NM · On-site

$15.75 - $21/hr

... Science, or a related field. * 2-5 years of relevant field experience in vegetation surveys ... Proficiency with ArcGIS Pro, QGIS, GPS equipment, and spatial data management. * Ability to prepare ...

Archaeologist II

Albuquerque, NM · On-site

$60K - $85K/yr

Collecting, documenting, and analyzing artifacts, spatial data, and field observations. * Utilizing ... Collaborating with environmental scientists, engineers, planners, and other specialists on ...

Collecting, documenting, and analyzing artifacts, spatial data, and field observations. * Utilizing ... Collaborating with environmental scientists, engineers, planners, and other specialists on ...

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Spatial Data Science information

See New Mexico salary details

$43.1K

$125.7K

$172K

How much do spatial data science jobs pay per year?

As of Aug 27, 2026, the average yearly pay for spatial data science in New Mexico is $125,705.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $133,200.00 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 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 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 does a spatial data scientist do?

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

What are popular job titles related to Spatial Data Science jobs in New Mexico?

For Spatial Data Science jobs in New Mexico, the most frequently searched job titles are:

What job categories do people searching Spatial Data Science jobs in New Mexico look for?

The top searched job categories for Spatial Data Science jobs in New Mexico are:

Infographic showing various Spatial Data Science job openings in New Mexico as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $125,705 per year, or $60.4 per hour.

Research Assistant/Staff

Albuquerque, NM • Remote


University of New Mexico

8.3

Company rating: 8.3 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

129th of 623 rated colleges and universities

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Full-time

Re-posted 17 days ago


Job description

 Formally established in 2020, the Center for the Advancement of Spatial Informatics Research and Education (ASPIRE) researches methods for the capture, analysis, and representation of spatial data characterizing physical and social phenomena, commonly referred to as Geographic Information Science (GIScience). GIScience is an inherently integrative field of study, relying on virtually all engineering fields for technological and theoretical advancements, and having applications in virtually all sciences. 
ASPIRE brings together faculty with expertise and cutting-edge research portfolios in a broad range of GIScience sub-fields, including spatial modeling, geo-visualization, remote sensing, and spatial statistics.

The Research Assistant will conduct LiDar Drone flights as a certified 107 remote pilot and will process data and produce reports for ASPIRE projects and the service cost center. 


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