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Machine Learning Geospatial Jobs in Missouri (NOW HIRING)

University of Missouri

Post Doctoral Fellow

Columbia, MO · On-site

$46K - $63K/yr

... analysis, geospatial data, and machine learning methods. No candidate is expected to have proficiency in all of these computer-based skills. Rather, the ideal candidate will be a well-rounded ...

GRVTY

Imagery Scientist (EO) - Senior

Saint Louis, MO · On-site +1

$160K - $190K/yr

... geospatial and imagery expertise and quantitative analysis to make recommendations that improve data curation and development in support of Machine Learning algorithm testing and evaluation. The ...

Bayer Inc.

Staff Software Engineer, Data

Creve Coeur, MO · On-site

$117K - $171K/yr

... of AI and machine learning at a global level. You will set technical direction, define how teams approach complex problems across precision agriculture data, geospatial imagery, and cloud ...

Bayer

Staff Software Engineer, Data

Creve Coeur, MO · On-site

$117K - $171K/yr

... of AI and machine learning at a global level. You will set technical direction, define how teams approach complex problems across precision agriculture data, geospatial imagery, and cloud ...

Intellectix

Data Scientist

Saint Louis, MO · On-site

This position supports the Geospatial Services & Solutions business area to provide high-quality ... Build predictive models and machine learning algorithms. * Combine models through ensemble modeling.

Intellectix

Data Scientist

Saint Louis, MO

This position supports the Geospatial Services & Solutions business area to provide high-quality ... Build predictive models and machine learning algorithms. * Combine models through ensemble modeling.

GRVTY

Senior Data Scientist

Saint Louis, MO

Familiarity with geospatial data science, GEOINT workflows, or multi-INT analysis. What Would Be ... Experience applying machine learning or artificial intelligence techniques to intelligence problems.

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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 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 the key skills and qualifications needed to thrive as a Machine Learning Geospatial specialist, and why are they important?

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 popular job titles related to Machine Learning Geospatial jobs in Missouri? For Machine Learning Geospatial jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Machine Learning Geospatial jobs in Missouri look for? The top searched job categories for Machine Learning Geospatial jobs in Missouri are:
What cities in Missouri are hiring for Machine Learning Geospatial jobs? Cities in Missouri with the most Machine Learning Geospatial job openings:
Machine Learning Geospatial jobs near you
Post Doctoral Fellow

Post Doctoral Fellow

University of Missouri

Columbia, MO • On-site

$46K - $63K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 18 days ago

University Of Missouri rating

7.2

Company rating: 7.2 out of 10

Based on 67 frontline employees who took The Breakroom Quiz

345th of 555 rated colleges and universities

Job description

Job Description
The Postdoctoral fellow will advance cropping systems research at the University of Missouri Plant Science Department in collaboration with the USDA ARS Cropping Systems and Water Quality Research Unit. This is a two-year position focused on advancing crop production and physiology through field experimentation, computation (statistics and machine learning), and process-based models. The successful candidate will have an inquisitive nature with a deep knowledge of many components listed in this posting and a strong desire for continual learning and growth professionally. We invite candidates to submit an application if able to start in the next three months and are excited to work at the intersection of genotype x environment x management.
Responsibilities:
The fellow will work to identify crop and system-based strategies that advance knowledge and discovery to minimize stress and maximize economic and environmental health. Specifically, this will be achieved through use of data from the past 5 years and on-going across several Missouri experiments. Research topics include: 1) productivity and economics of intensified crop rotations, 2) management decisions based on crop phenology, 3) physiological and growth response to late-season stressors, and 4) plausibility of double-crop systems. The fellow is expected to write four papers, with three accepted and one submitted, during these two years. In addition to publishing in refereed journals, the fellow will develop lay materials to transfer key findings to farmers and agribusiness.
Qualifications
Minimum Qualification:
PhD, by time of appointment. Candidates need to have a PhD in agronomy, agroecology, ecology, soil science, natural resources, environmental science, agricultural engineering, statistics, data science, or similar discipline.
Candidates will be evaluated on:
Candidates need to have excellent written and oral communication skills in English. They must be able to work effectively independently, in teams, and across disciplines.
Candidates must have an excellent understanding of the processes underlying plant, soil, and environment within an agricultural setting.
Candidates must have a strong command of data synthesis, modeling, and/or machine learning. It is beneficial to have experience in several of the following areas: data processing, statistical analyses, R software, regression models, process-based models such as DSSAT or APSIM, Bayesian statistical analysis, geospatial data, and machine learning methods. No candidate is expected to have proficiency in all of these computer-based skills. Rather, the ideal candidate will be a well-rounded individual with a high aptitude to learn during the fellowship.
Application Materials
Apply online at https://hr.missouri.edu/job-openings , Job ID# 59893.
To apply, submit a single PDF file that includes 1) a letter of interest describing how your skills and interests make you a strong candidate for this position; 2) a current CV; and 3) contact information for three professional references.
Closing Date:
Applications will be received until midnight (CST) June 30, 2026. However, review of applications will begin 15 days after the job was posted.
Contact:
Reach out with questions about this postdoctoral fellowship to Dr. Andre Froes de Borja Reis, Assistant Professor and State Extension Specialist in Soybean Agronomy, areis@missouri.edu or 573-882-4771.
Sponsorship Information
Visa Sponsorship Information:
Applicants must be authorized to work in the United States. The University will not sponsor applicants for this position for employment visas.
Benefit Eligibility
This position is eligible for University benefits. As part of your total compensation, the University offers a comprehensive benefits package, including medical, dental and vision plans, retirement, and educational fee discounts for all four UM System campuses. For additional information on University benefits, please visit the Faculty & Staff Benefits website at https://www.umsystem.edu/totalrewards/benefits .
Equal Employment Opportunity
The University of Missouri is an Equal Opportunity Employer .
To request ADA accommodations, please call the Director of Accessibility and ADA at 573-884-7278.

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About University of Missouri

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The University of Missouri, based in Columbia, MO, US; is a public, land-grant research institution with an established reputation in academic excellence, industry relevance, and societal impact. Founded in 1839, it was the first public university located west of the Mississippi River. The institution spans various industries in the education sector with its multitude of undergraduate, graduate, and professional degree programs across various disciplines. The University's mission is centered on improving lives, enhancing communities, advancing health, and fostering excellence through its teaching, research, and engagement activities. U-M has some significant achievements under its belt including pioneering the world's first school of journalism and being one of the only six public universities in the US that accommodates medicine, veterinary medicine, and law in one campus.

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Columbia, MO, US

Year founded

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