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Remote Sensing Scientist Jobs in Kansas (NOW HIRING)

This individual will lead the scientific foundation of our Fuel Detection Model, the core engine ... Deep expertise in remote sensing and geospatial analysis, including working with satellite imagery ...

You have a background in wildfire science, forestry, or remote sensing * Strong background in deep learning, computer vision, or remote sensing * Skilled in designing end-to-end ML systems - from ...

Intermediate knowledge of HPC / Data Science * Water Resources Engineering Modeling Software ... Experience with data processing imagery and LiDAR from web services, UAS, or other remote sensing ...

Meteorologist

Dodge City, KS · On-site +1

$40K/yr

Degree in Meteorology, Atmospheric Science, or another natural science major that includes: * At ... hours in remote sensing of the atmosphere and/or instrumentation * 6 semester hours of physics ...

Meteorologist

Goodland, KS · On-site +1

$40K/yr

Degree in Meteorology, Atmospheric Science, or another natural science major that includes: * At ... hours in remote sensing of the atmosphere and/or instrumentation * 6 semester hours of physics ...

Remote Sensing Scientist information

See Kansas salary details

$74.5K

$113.3K

$152.5K

How much do remote sensing scientist jobs pay per year?

As of Aug 23, 2026, the average yearly pay for remote sensing scientist in Kansas is $113,293.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $128,000.00 per year, depending on experience, location, and employer.

What is a remote sensing scientist?

Remote Sensing Scientists are professionals who use satellite or airborne sensor data to analyze and interpret information about the Earth's surface and atmosphere. They apply techniques from physics, geography, and computer science to process and analyze remotely sensed images for applications such as environmental monitoring, agriculture, urban planning, and disaster management. Their work often involves using software to manipulate geospatial data and create maps or models that inform decision-making. Remote Sensing Scientists may work in government agencies, research institutions, or private industry, and often collaborate with other scientists and engineers.

What does a remote sensing scientist do?

Remote sensing scientists analyze data using sensors to solve problems related to local issues like urban planning to global complications like natural resource management. As a remote sensing scientist, your responsibilities include using statistical analysis or image analysis software to analyze data acquired by aircraft, satellites, and other platforms. You monitor atmospheric changes, better understand geospatial information, and even help influence decision making regarding fair and equitable land use. Remote sensing scientists are closely involved in innumerable fields.

What are the key skills and qualifications needed to thrive as a remote sensing scientist, and why are they important?

To thrive as a Remote Sensing Scientist, you need a strong background in geospatial analysis, image processing, and a relevant degree in fields such as geography, environmental science, or engineering. Familiarity with GIS software (like ArcGIS or QGIS), remote sensing tools (such as ENVI or ERDAS Imagine), and programming languages (Python, R) is typically required. Analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting data and presenting findings. These competencies are vital for accurately analyzing earth observation data, supporting decision-making, and ensuring the reliability of scientific conclusions.

What are some typical challenges remote sensing scientists face when working with large datasets?

Remote Sensing Scientists often work with massive amounts of satellite or aerial imagery, which can present challenges related to data storage, processing speed, and data quality management. Ensuring the accuracy of image analysis and integrating data from multiple sensor types or platforms can also be complex. To address these issues, scientists frequently rely on high-performance computing, cloud-based platforms, and advanced algorithms for data preprocessing and analysis. Collaborating closely with data engineers and software developers is common to streamline workflow and maintain data integrity.

What is the difference between Remote Sensing Scientist vs GIS Analyst?

AspectRemote Sensing ScientistGIS Analyst
Required CredentialsBachelor's/Master's in Remote Sensing, Geospatial Science, or related fieldsBachelor's/Master's in Geography, GIS, or related fields
Work EnvironmentResearch labs, government agencies, environmental firmsUrban planning, environmental consulting, government agencies
Industry UsageSatellite data analysis, environmental monitoringMapping, spatial data analysis, infrastructure planning
Common Search IntentRemote sensing data interpretation, satellite imagery analysisGIS mapping, spatial data management

While both roles involve geospatial data, Remote Sensing Scientists focus on analyzing satellite and aerial imagery to monitor environmental changes, whereas GIS Analysts primarily work with geographic information systems to create maps and analyze spatial data for planning and decision-making.

Does remote sensing scientist pay well?

Remote sensing scientists typically earn competitive salaries that vary based on experience, education, and location. According to industry data, median salaries range from $60,000 to over $100,000 annually, with higher pay often associated with advanced skills in GIS, image analysis, and remote sensing software. Many roles also offer benefits such as flexible schedules and opportunities for professional development.

How much do remote sensing scientists earn?

Remote sensing scientists typically earn a median annual salary of around $70,000 to $100,000, depending on experience, education, and location. Advanced skills in GIS, image analysis, and programming can lead to higher compensation, especially in research or industry roles.

What are popular job titles related to Remote Sensing Scientist jobs in Kansas?

For Remote Sensing Scientist jobs in Kansas, the most frequently searched job titles are:

Infographic showing various Remote Sensing Scientist job openings in Kansas as of August 2026, with employment types broken down into 70% Full Time, and 30% Part Time. Highlights an 100% Remote job distribution, with an average salary of $113,293 per year, or $54.5 per hour.

Staff Data Scientist - Wildfire

Overstory

On-site, Remote

Full-time

Posted 5 days ago


Job description

Role & Team

We are excited to add a Staff Data Scientist, Wildfire to our team. This individual will lead the scientific foundation of our Fuel Detection Model, the core engine that translates satellite and environmental data into an understanding of vegetation structure, fuel loads, and wildfire risk.
Working alongside ML engineers, and a product team, you'll define accuracy for our models, design the research and validation methods that prove it, and ensure our modeling choices are grounded in fire science and remote sensing fundamentals. This is a great opportunity for someone who is energized by open scientific questions with direct real-world stakes, and who wants their research to shape how utilities prevent catastrophic wildfires.

Time Zone Requirement: North America (NST, AST, EST, CST, MST, PST)

What You'll Do
  • Lead research into how vegetation structure, fuel conditions, and wildfire risk can be estimated from satellite, LiDAR, and environmental data across diverse geographies
  • Design rigorous validation and evaluation methodologies, including ground-truth strategies, uncertainty quantification, and error analysis tied to real-world impact
  • Prototype and refine ML modeling approaches, then partner with ML engineers to translate them into production systems
  • Integrate established fire science, such as fuel models and fire behavior frameworks, with data-driven methods
  • Define scientific standards for experimentation, reproducibility, and model interpretability across the modeling organization
  • Communicate research findings clearly to engineers, product teams, customers, and the broader wildfire science community
  • Mentor ML engineers on scientific methodology and domain reasoning
Skills & Experience
  • 8+ years of applied research or data science experience in wildfire science, fire ecology, forestry, remote sensing, atmospheric science, or a related quantitative field
  • Deep expertise in remote sensing and geospatial analysis, including working with satellite imagery and large-scale environmental datasets
  • Strong statistical modeling and machine learning skills in Python, with tools like GeoPandas, scikit-learn, PyTorch, or XGBoost
  • Track record of designing validation studies and evaluation frameworks for environmental or geospatial models
  • Excellent communication skills, with the ability to make complex scientific work legible across technical and non-technical audience
Nice To Have
  • Familiarity with fire behavior or fuels modeling frameworks (e.g., Rothermel-based models, LANDFIRE fuel classifications)
  • Experience integrating physics-based models with ML, or with active learning and uncertainty quantification
  • Peer-reviewed publications in wildfire science, remote sensing, or environmental modeling
  • Familiarity with GCP, Vertex AI, or similar cloud-based platforms
  • Experience in remote-first or globally distributed team

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer
  • Competitive, location-specific compensation and benefits 
  • Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
  • Home office stipend, co-working and ongoing education budgets 
  • A company culture that genuinely embodies each of our core values
  • To be part of truly mission-driven work that reduces wildfires, protects earth's natural resources and helps solve our climate crisis