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Geospatial Data Scientist Jobs in Missouri (NOW HIRING)

Jobgether

$80K - $110K/yr

Requirements: * 5+ years of professional experience as a Machine Learning Engineer, Data Scientist ... Solid understanding of geospatial data structures, formats, processing workflows, and analysis ...

GRVTY

Data Scientist, Expert

Arnold, MO

Apply AI/ML techniques to enhance geospatial analysis capabilities and improve accuracy in data extraction from various sources. * Develop API-based integration solutions to improve data exchange ...

GRVTY

Data Scientist, Mid

Arnold, MO

This position performs services requiring specialized expertise in geospatial data analysis, automation, data management and system administration. Supports a variety of data issues to include ...

GRVTY

Data Scientist, Mid

Arnold, MO · On-site

This position performs services requiring specialized expertise in geospatial data analysis, automation, data management and system administration. Supports a variety of data issues to include ...

GRVTY

Data Scientist, Expert

Arnold, MO · On-site

Apply AI/ML techniques to enhance geospatial analysis capabilities and improve accuracy in data extraction from various sources. * Develop API-based integration solutions to improve data exchange ...

Esri

Data Scientist I

Saint Louis, MO · On-site

$70K - $110K/yr

We're seeking a Data Scientist who combines technical expertise with strong interpersonal skills to ... Implement best practices and patterns for geospatial machine learning and develop reusable ...

GeoYeti

Senior SAR Imagery Scientist

Saint Louis, MO · Remote

$190K - $235K/yr

Overview Senior SAR Imagery Scientist Springfield, VA or St. Louis, MO Active TS/SCI eligibility ... Strong foundation in remote sensing principles and geospatial data processing * Clear communicator ...

Bayer

$71K - $135K/yr

The Science Technical Community is focused on creating a competitive advantage for Bayer and our ... geospatial data manipulation and visualization to derive insights from agricultural or ...

Bayer Inc.

Data Analyst

Creve Coeur, MO

$7/hr

The Science Technical Community is focused on creating a competitive advantage for Bayer and our ... Experience performing geospatial data manipulation and visualization to derive insights from ...

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All JobsGeospatial Data Scientist JobsGeospatial Data Scientist Jobs in Missouri

Geospatial Data Scientist information

See Missouri salary details

$35.2K

$115.1K

$184.3K

How much do geospatial data scientist jobs pay per year?

As of Aug 23, 2026, the average yearly pay for geospatial data scientist in Missouri is $115,129.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,400.00 and $127,600.00 per year, depending on experience, location, and employer.

What is a geospatial data scientist?

A Geospatial Data Scientist analyzes spatial and geographic data to extract insights, create predictive models, and support decision-making. They use tools like GIS, remote sensing, machine learning, and statistical analysis to process location-based data. Their work spans various industries, including urban planning, environmental monitoring, agriculture, and logistics. By leveraging spatial data, they help optimize operations, manage resources, and solve complex geographic problems.

What does a geospatial data scientist do?

As a Geospatial Data Scientist, your daily tasks often involve collecting, cleaning, and analyzing spatial datasets using GIS tools and programming languages. You may be responsible for developing spatial models, visualizing geographic data through interactive maps, and generating reports to help guide strategic decisions. Collaboration with professionals from engineering, urban planning, or environmental science teams is common, requiring you to communicate complex analyses in a clear and actionable manner. Additionally, you might participate in project meetings to align your work with organizational goals and stakeholder needs. This dynamic role blends technical analysis with communication and teamwork, making each day varied and intellectually stimulating.

What are the key skills and qualifications needed to thrive as a geospatial data scientist?

Geospatial Data Scientists require expertise in spatial analysis, statistics, and data modeling, typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), programming languages like Python or R, and familiarity with spatial databases are often expected, while certifications in GIS can be advantageous. Strong problem-solving abilities, collaboration, and effective communication skills help professionals translate complex data into actionable insights and work well with diverse teams. Mastery of these skills ensures accurate geospatial analyses and supports informed, data-driven decision making in various industries.

How much does a geospatial data scientist make?

A geospatial data scientist's salary typically ranges from $70,000 to $130,000 annually, depending on experience, education, location, and industry. Senior roles or those with specialized skills in GIS tools and programming may earn higher compensation.

Is geospatial data scientist still in demand?

Yes, geospatial data scientists are in high demand due to the increasing use of geographic information systems (GIS), remote sensing, and spatial analysis across industries such as urban planning, environmental management, and transportation. The role often requires skills in programming, data analysis, and tools like Python, R, and GIS software, with strong job growth projected in the coming years.

What are the most commonly searched types of Geospatial Data Scientist jobs in Missouri?

The most popular types of Geospatial Data Scientist jobs in Missouri are:

What are popular job titles related to Geospatial Data Scientist jobs in Missouri?

For Geospatial Data Scientist jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Geospatial Data Scientist jobs in Missouri look for?

The top searched job categories for Geospatial Data Scientist jobs in Missouri are:

What cities in Missouri are hiring for Geospatial Data Scientist jobs?

Cities in Missouri with the most Geospatial Data Scientist job openings:

Geospatial Data Scientist jobs near you
Infographic showing various Geospatial Data Scientist job openings in Missouri as of August 2026, with employment types broken down into 100% Full Time. Highlights an 84% In-person, and 16% Remote job distribution, with an average salary of $115,129 per year, or $55.4 per hour.

Senior Geospatial Machine Learning Engineer

Jobgether

On-site, Remote

$80K - $110K/yr

Full-time

Posted 15 days ago

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Geospatial Machine Learning Engineer based in Netherlands.

Join a fully remote, mission-driven climate technology environment where machine learning and satellite imagery are used to address critical infrastructure challenges.
As part of the Vegetation Modeling team, you will build advanced ML solutions that identify vegetation-related risks before they contribute to wildfires or power outages.
You will work with large-scale geospatial datasets, satellite and aerial imagery, computer vision, and deep learning to create production-ready intelligence products.
The role combines hands-on engineering with technical ownership, giving you the opportunity to lead projects from initial planning through delivery.
You will collaborate with teams across Europe and the Americas, influencing data pipelines, platform architecture, model evaluation, and product delivery.
Your work will directly contribute to improving grid resilience while applying technology to complex environmental and climate challenges.
This is an opportunity for a senior ML professional who wants meaningful technical challenges and measurable real-world impact.

Accountabilities
  • Develop and deploy new vegetation intelligence products using machine learning, deep learning, computer vision, geospatial Python libraries, and large-scale satellite or aerial imagery.
  • Explore geospatial datasets, identify opportunities for model improvement, optimize existing ML solutions, and troubleshoot production issues.
  • Maintain and enhance existing vegetation modeling products to improve accuracy, reliability, scalability, and overall impact.
  • Lead technical projects end-to-end, from defining objectives and planning implementation through execution, delivery, and evaluation.
  • Develop measurement frameworks, evaluation tooling, and performance metrics that enable data-driven decisions about model quality and impact.
  • Monitor production models and investigate performance issues using appropriate observability, monitoring, and debugging tools.
  • Work closely with upstream data ingestion teams to influence data pipelines, processing workflows, and platform architecture.
  • Partner with downstream product and delivery teams to ensure geospatial ML outputs can be effectively integrated into customer-facing solutions.
  • Use tools such as QGIS, Dagster, Sentry, Grafana, or equivalent platforms to analyze data, manage workflows, monitor systems, and diagnose issues.
  • Communicate technical findings, project progress, model performance, and business impact clearly to technical and non-technical stakeholders.
  • Contribute to engineering and ML best practices across a distributed team working across Europe and the Americas.
  • Help translate complex environmental and geospatial problems into scalable machine learning solutions that support climate resilience and critical infrastructure.
Requirements:
  • 5+ years of professional experience as a Machine Learning Engineer, Data Scientist, or in a closely related role, with demonstrated experience building and deploying production machine learning or deep learning models.
  • Proven experience developing computer vision or deep learning models using satellite or aerial imagery.
  • Strong proficiency in Python and geospatial Python libraries such as rasterio, geopandas, shapely, GDAL, or equivalent technologies.
  • Solid understanding of geospatial data structures, formats, processing workflows, and analysis techniques.
  • Professional experience with ML and deep learning frameworks such as PyTorch, TensorFlow, scikit-learn, or comparable tools.
  • Experience designing, implementing, or maintaining data pipelines using orchestration and workflow tools such as Dagster, Airflow, dbt, or equivalent systems.
  • Experience with QGIS or comparable geospatial visualization and analysis software.
  • Strong understanding of model evaluation, performance measurement, monitoring, and debugging in production environments.
  • Ability to work effectively with large-scale, complex datasets and translate technical findings into practical product or business decisions.
  • Strong project ownership skills, with the ability to independently drive initiatives from planning through execution and delivery.
  • Excellent communication and collaboration skills, particularly in distributed and cross-functional environments.
  • Experience with multispectral or hyperspectral satellite imagery is a strong advantage.
  • Background in vegetation analysis, forestry, agriculture, environmental monitoring, or related geospatial applications is highly valued.
  • Familiarity with observability and monitoring tools such as Grafana, Sentry, Prometheus, or similar platforms is a plus.
  • A genuine interest in climate technology, environmental applications, and using advanced technology to solve complex real-world problems is highly desirable.
  • Candidates should be comfortable working in a fully remote environment and collaborating across multiple time zones.
Benefits:
  • Fully remote working environment.
  • Opportunity to work on technology with direct applications in climate action, wildfire prevention, and electrical grid resilience.
  • Meaningful ownership of machine learning products and the opportunity to lead projects from concept through production.
  • Collaboration with a geographically distributed team spanning Europe and the Americas.
  • Exposure to advanced satellite imagery, geospatial data, computer vision, and large-scale machine learning systems.
  • High-impact technical challenges involving real-world environmental and infrastructure problems.
  • Competitive senior-level compensation package expected, commensurate with experience.
  • Opportunity to contribute to the development of production ML systems rather than purely experimental or research-focused models.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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