ZipRecruiter

Log In

1

Machine Learning Geospatial Jobs in Vermont (NOW HIRING)

All JobsMachine Learning Geospatial JobsMachine Learning Geospatial Jobs in Vermont

Machine Learning Geospatial information

What does a Machine Learning Geospatial professional do?

A Machine Learning Geospatial professional uses machine learning techniques to analyze and interpret geospatial data, such as satellite imagery, maps, and GPS data. Their work involves building and training models to detect patterns, make predictions, and solve spatial problems in fields like agriculture, urban planning, disaster response, and environmental monitoring. These professionals often collaborate with data scientists and GIS (Geographic Information Systems) specialists to extract actionable insights from large and complex geospatial datasets. Their skills are crucial for automating tasks such as image classification, land cover mapping, and object detection in geographic contexts.

What are the key skills and qualifications needed to thrive as a Machine Learning Geospatial professional?

To thrive as a Machine Learning Geospatial specialist, you need a strong background in machine learning, geospatial analysis, programming (Python, R), and a relevant degree in computer science, geography, or a related field. Familiarity with GIS software (e.g., ArcGIS, QGIS), remote sensing tools, and cloud platforms like Google Earth Engine or AWS is typically required. Analytical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with multidisciplinary teams. These skills and qualities are crucial for developing accurate geospatial models and delivering actionable insights from complex spatial data.

What are some common challenges faced by Machine Learning Geospatial professionals when integrating spatial data into predictive models?

Machine Learning Geospatial professionals often encounter challenges such as managing large and complex spatial datasets, ensuring data quality and consistency, and handling spatial autocorrelation that can bias model results. Additionally, integrating diverse data sources—like satellite imagery, sensor data, and GIS layers—requires advanced pre-processing and domain knowledge. Collaborating with GIS analysts and domain experts is usually essential to develop robust models that provide actionable insights.

What is the difference between Machine Learning Geospatial vs GIS Analyst?

AspectMachine Learning GeospatialGIS Analyst
Required CredentialsBachelor's or higher in Computer Science, Data Science, or related fields; knowledge of machine learning and geospatial dataBachelor's in Geography, GIS, or related fields; proficiency in GIS software
Work EnvironmentTech companies, data science teams, research institutionsGovernment agencies, urban planning, environmental firms
Industry UsageData-driven geospatial analysis, predictive modeling, AI applicationsMapping, spatial data management, spatial analysis

Machine Learning Geospatial professionals focus on applying machine learning techniques to analyze geospatial data, often working with large datasets and developing predictive models. GIS Analysts primarily handle spatial data management, mapping, and analysis using GIS software. While both roles work with geospatial data, Machine Learning Geospatial roles emphasize data science and AI, whereas GIS Analysts focus on spatial information management and visualization.

What are popular job titles related to Machine Learning Geospatial jobs in Vermont?

For Machine Learning Geospatial jobs in Vermont, the most frequently searched job titles are:

What job categories do people searching Machine Learning Geospatial jobs in Vermont look for?

The top searched job categories for Machine Learning Geospatial jobs in Vermont are:

What cities in Vermont are hiring for Machine Learning Geospatial jobs?

Cities in Vermont with the most Machine Learning Geospatial job openings:

Machine Learning Geospatial jobs near you
Infographic showing various Machine Learning Geospatial job openings in Vermont as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution.

AI/ML Ecosystem Data Analyst

The University of Vermont

Burlington, VT • On-site

$80K - $95K/yr

Full-time

Posted 10 days ago

University Of Vermont rating

8.1

Company rating: 8.1 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

169th of 627 rated colleges and universities

Job description

AI/ML Ecosystem Data Analyst
Posting Summary
Serve as the AI/ML Ecosystem Data Analyst within the USGS Research Cooperative Unit at UVM ,and in collaboration with the Spatial Analysis Lab ( SAL ). The primary role of this position is to analyze ecological data and design, build, and operationalize AI/ML workflows that collect, process, and derive insight from heterogeneous data sources, including wildlife imagery, bioacoustics recordings, geospatial and remotely sensed data, sensor networks, and field observations. Develop, train, evaluate, and deploy AI/ML models for mapping, classification, and detection of wildlife and other features, and build the data pipelines, databases, and R Shiny or comparable interfaces that make results reproducible, maintainable, and accessible to researchers, partners, and the public. Support the AI/ML branch of RSENR within the Cooperative Unit and SAL , contribute to ecosystem monitoring efforts, and help oversee the Alliance for Monitoring Biodiversity and Ecosystems Remotely ( AMBER ) program. Work under the direction of the USGS Research Cooperative Unit Leader and collaborate with the SAL Director, RSENR , and other partners on grant writing, business development, and research initiatives, while independently pursuing outside funding opportunities. Partner with geospatial analysts and the development team lead on research and development of new AI/ML methods and models
Minimum Qualifications (or equivalent combination of education and experience)
- PhD in Computer Science, Wildlife Biology, Ecology, Data Science, Bioinformatics, or a closely related discipline, and four years related professional experience.
- Demonstrated expertise in data science, machine learning, and AI applications.
- Strong proficiency in relational database design and management, including stand-alone programs such as SQLite and served databases such as SQL or Postgres.
- Experience with APIs, web services, Power Automate, Teams, and Sharepoint for workflow integration.
- Strong record of interdisciplinary collaboration and scientific productivity.
- Experience managing complex technical or research projects, including grant writing.
- Experience with cloud-native infrastructure and scalable AI workflows, focused primarily on the R and Python coding languages.
- Substantial experience in working with the public and agency monitoring partners.
Desirable Qualifications
- Postdoctoral experience preferred
- High proficiency in public outreach and instruction desired
- Supervisory or personnel management experience desired
Anticipated Pay Range
$80,000 - $95,000
Other Information
Special Conditions
A probationary period may be required, Contingent on continued funding, Occasional evening and/or weekends required (if non-exempt position, may result in overtime), Travel to and from worksites required, This position is eligible for a hybrid schedule with an option to split time between campus and elsewhere, in accordance with the university telecommuting policy, Background Check required for this position

What University Of Vermont employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply