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Remote Geostatistics Jobs (NOW HIRING)

Geologist

Sandy, UT · On-site +1

Undergraduate or Graduate Degree in Geology, Geostatistics, Geological or Mining Engineering or ... at times to remote locations * Fluent and effective spoken and technical writing in English.

Experience with GIS/geostatistics and/or complex survey design * Knowledge management experience ... Location Fully remote within the USA, with travel once or twice a year for retreats and conferences.

Remote Geostatistics information

What is the difference between Remote Geostatistics vs Remote GIS Specialist?

AspectRemote GeostatisticsRemote GIS Specialist
Required CredentialsDegree in Geostatistics, Geology, or related field; proficiency in statistical softwareDegree in Geography, GIS, or related; expertise in GIS software and spatial analysis
Work EnvironmentData analysis, statistical modeling, and spatial data interpretationMapping, spatial data management, and GIS software application
Industry UsageMining, oil & gas, environmental consulting

Remote Geostatistics focuses on statistical analysis of spatial data, while Remote GIS Specialists primarily handle mapping and spatial data management. Both roles often require similar educational backgrounds and are used across industries like mining and environmental consulting. Understanding these differences helps job seekers target the right position based on their skills and career goals.

What are remote geostatistics?

Remote geostatistics is the application of statistical methods to analyze spatial data collected remotely, often using technologies like satellites, drones, or remote sensors. This field combines geostatistics—used to model and predict spatial patterns—with remote sensing to study environmental phenomena, resource exploration, and land use mapping. Professionals in remote geostatistics interpret spatial data to provide insights for industries such as mining, agriculture, and environmental monitoring. Their work often involves data processing, mapping, and creating predictive models to support decision-making.

What are some common challenges faced by professionals working in remote geostatistics, and how can they be effectively addressed?

One of the main challenges in remote geostatistics is maintaining effective communication and collaboration with multidisciplinary teams spread across different locations. Data transfer and management can also be complex due to large geospatial datasets and varied data sources. To address these challenges, professionals often use specialized software for secure data sharing, establish regular virtual meetings, and create clear documentation for workflows. Developing strong time management and self-motivation skills is also crucial for success in a remote setting.

What are the key skills and qualifications needed to thrive as a Remote Geostatistics professional, and why are they important?

To thrive as a Remote Geostatistics professional, you need a strong background in statistics, spatial analysis, and earth sciences, often supported by a degree in geology, geography, or a related field. Familiarity with geostatistical modeling software (such as ArcGIS, Surfer, or Python libraries like GeoPandas), remote sensing tools, and data visualization platforms is typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret complex data and convey insights to multidisciplinary teams. These skills ensure accurate spatial data analysis and support data-driven decision-making in fields such as environmental management, mining, and resource exploration.
More about Remote Geostatistics jobs
What cities are hiring for Remote Geostatistics jobs? Cities with the most Remote Geostatistics job openings:
What are the most commonly searched types of Geostatistics jobs? The most popular types of Geostatistics jobs are:
What states have the most Remote Geostatistics jobs? States with the most job openings for Remote Geostatistics jobs include:
Infographic showing various Remote Geostatistics job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 2% Internship, 3% As Needed, 7% Temporary, 85% Contract, and 2% Nights. Highlights an 100% Hybrid job distribution.
Postdoctoral Research Associate in Geospatial AI (GeoAI) and Forest Health

Postdoctoral Research Associate in Geospatial AI (GeoAI) and Forest Health

Lincoln University

Jefferson City, MO • On-site, Remote

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

PURPOSE:

The Postdoctoral Research Associate will engage in research and development of a GeoAI-powered early warning system for forest health by integrating multi-source geospatial data, including satellite imagery, UAV-based LiDAR and multispectral data, and environmental datasets.

This position supports a USDA-NIFA funded project focused on detecting early indicators of forest stress, pest infestation, and environmental disturbances using advanced artificial intelligence and geospatial analytics. The role contributes to research, education, and extension activities in Missouri and supports the broader mission of advancing innovation in geospatial science and environmental monitoring.

ESSENTIAL JOB FUNCTIONS, DUTIES, & RESPONSIBILITIES:

  • Plan and implement research activities focused on early detection of forest stress, disturbance, and ecological change using geospatial analytics and artificial intelligence. 
  • Compile, collect, clean, and process geospatial and ancillary datasets from multiple sources, including satellite imagery, UAV-based LiDAR, multispectral imagery, and environmental data. 
  • Develop, train, and optimize GeoAI models using machine learning and deep learning techniques for spatial analysis and predictive modeling.
  • Validate GeoAI models through field verification and collaboration with the Missouri Ozark Forest Ecosystem Project (MOFEP). 
  • Develop decision-support tools and interfaces that translate complex geospatial outputs into usable information for stakeholders. 
  • Contribute to peer-reviewed publications, conference presentations, and technical documentation required for project deliverables. 
  • Mentor graduate and undergraduate students involved in research activities. 
  • Collaborate with interdisciplinary teams across research, extension, and education initiatives. 
  • Maintain accurate records of research activities, methodologies, and results. 
  • Perform other duties as assigned by the supervisor in support of project goals.

KNOWLEDGE, SKILLS, & ABILITIES:

  • Strong understanding of Geospatial Artificial Intelligence (GeoAI), including integration of machine learning and deep learning methods with geospatial and environmental datasets. 
  • Proficiency in programming languages such as Python or R, including experience with relevant libraries for data analysis, modeling, and visualization. 
  • Knowledge of spatial data processing, geostatistics, and remote sensing techniques. 
  • Familiarity with multi-source data integration and spatial modeling workflows. 
  • Experience working with geospatial software and tools such as GIS platforms, remote sensing tools, and data processing frameworks. 
  • Ability to interpret scientific data and translate findings into actionable insights. 
  • Strong analytical, problem-solving, and critical thinking skills. 
  • Effective written and verbal communication skills for technical and academic audiences. 
  • Ability to work both independently and collaboratively within interdisciplinary research teams. 
  • Strong organizational skills and ability to manage multiple tasks and deadlines.

QUALIFICATIONS:

  • Ph.D. in Geospatial Science, Geography, Remote Sensing, Data Science, Forestry, Environmental Science, or a closely related field.
  • Valid driver's license. 
  • Must have or be able to obtain a Remote Pilot Certificate (FAA Part 107). 
  • Demonstrated experience conducting independent research.
  • Ability to manage research timelines and deliverables within a grant-funded project.

PREFERRED QUALIFICATIONS:

  • Experience working with UAV or LiDAR data for environmental or forestry applications. 
  • Background in applying machine learning methods to geospatial or ecological datasets. 
  • Demonstrated record of peer-reviewed publications or scientific research dissemination.
  • Ability to work independently and manage projects with minimal supervision.
  • Strong organizational and problem-solving skills, particularly when working with large or complex datasets.
  • Experience collaborating across interdisciplinary teams.

PHYSICAL DEMANDS:

  • Work will be conducted in both office and outdoor field environments.
  • Fieldwork may involve walking in forested terrain and working in variable weather conditions.
  • Ability to lift and transport equipment weighing up to 40 pounds.
  • Ability to travel to research sites as needed.

This job description is not intended to be a complete list of all responsibilities, duties or skills required for the job and is subject to review and change at any time, with or without notice, in accordance with the needs of Lincoln University. Since no job description can detail all the duties and responsibilities that may be required from time to time in the performance of a job, duties and responsibilities that may be inherent in a job, reasonably required for its performance, or required due to the changing nature of the job shall also be considered part of the jobholder's responsibility.