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Geospatial Data Science Jobs (NOW HIRING)

Demonstrated experience and proficiency with data science techniques including (but not limited to ... Knowledge of the National System for Geospatial-Intelligence (NSG) tasking, collection, processing ...

Senior Geospatial Data Engineer

Mclean, VA

$107K - $145K/yr

Bachelor's degree in Geography, GIS, Computer Science, Data Science, Engineering, or a related technical discipline. * 12+ years of professional experience in geospatial technology, software ...

Senior Geospatial Data Engineer

Mclean, VA · On-site

$107K - $145K/yr

Bachelor's degree in Geography, GIS, Computer Science, Data Science, Engineering, or a related technical discipline. * 12+ years of professional experience in geospatial technology, software ...

Your Growth You'll expand your geospatial tradecraft into applied data science and AI/ML data ... operations - developing skills in quantitative analysis, spatial statistics, and ML-informed ...

Your Growth You'll expand your geospatial tradecraft into applied data science and AI/ML data ... operations -- developing skills in quantitative analysis, spatial statistics, and ML-informed ...

Geospatial Analyst III

Glen Allen, VA · On-site

$75K - $97K/yr

Bachelor's degree in computer science, data science, GIS or other relevant geospatial or data science related field * At least 5 years' experience working with Esri technology, particularly with Esri ...

Geospatial Analyst III

Glen Allen, VA · Hybrid

$75K - $97K/yr

Bachelor's degree in computer science, data science, GIS or other relevant geospatial or data science related field * At least 5 years' experience working with Esri technology, particularly with Esri ...

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Geospatial Data Science information

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$22K

$77.5K

$122K

How much do geospatial data science jobs pay per year?

As of Jul 12, 2026, the average yearly pay for geospatial data science in the United States is $77,494.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,500.00 and $80,000.00 per year, depending on experience, location, and employer.

How does a Geospatial Data Scientist typically collaborate with other departments or teams within an organization?

Geospatial Data Scientists often work closely with professionals from diverse departments such as urban planning, environmental science, IT, and business analytics. Collaboration usually involves sharing spatial insights, integrating geospatial data with other datasets, and contributing to interdisciplinary projects that require spatial analysis or mapping. Effective communication is crucial, as you'll translate complex geospatial findings into actionable recommendations for non-technical stakeholders. This cross-functional teamwork not only broadens your understanding of organizational goals but also enhances the impact and visibility of geospatial analyses.

What is the difference between Geospatial Data Science vs GIS Analyst?

AspectGeospatial Data ScienceGIS Analyst
Required CredentialsDegree in Data Science, Geography, or related; often includes programming skillsDegree in Geography, GIS, or related; GIS certifications common
Work EnvironmentData analysis, modeling, programming, often in tech or research settingsMapping, spatial data management, using GIS software in various industries
Employer & Industry UsageTech companies, research institutions, government agencies focusing on spatial data analysisUrban planning, environmental agencies, utilities, and government agencies

While both roles work with spatial data, Geospatial Data Science emphasizes data analysis, modeling, and programming skills to extract insights from geospatial data. GIS Analysts focus more on mapping, data management, and using GIS software for spatial analysis. The roles often overlap but differ mainly in technical focus and application areas.

What are the key skills and qualifications needed to thrive as a Geospatial Data Scientist, and why are they important?

To thrive as a Geospatial Data Scientist, you need a solid background in statistics, spatial analysis, and programming, typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), spatial databases, and coding languages like Python or R is essential, and certifications in GIS can be advantageous. Strong problem-solving skills, attention to detail, and effective communication help translate complex spatial data into actionable insights for diverse stakeholders. These skills ensure accurate data analysis, innovative solutions, and impactful decision-making in fields reliant on geographic information.

What is geospatial data science?

Geospatial data science is an interdisciplinary field that focuses on analyzing and interpreting data that has a geographic or spatial component. It combines techniques from data science, statistics, and geographic information systems (GIS) to extract insights, identify patterns, and solve problems related to location-based data. Professionals in this field work with mapping, remote sensing, spatial analysis, and visualization tools to support decision-making in areas like urban planning, environmental monitoring, and logistics.
More about Geospatial Data Science jobs
What cities are hiring for Geospatial Data Science jobs? Cities with the most Geospatial Data Science job openings:
What are the most commonly searched types of Geospatial Data Science jobs? The most popular types of Geospatial Data Science jobs are:
What states have the most Geospatial Data Science jobs? States with the most job openings for Geospatial Data Science jobs include:
Infographic showing various Geospatial Data Science job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $77,494 per year, or $37.3 per hour.
Data Scientist Geospatial Analytics

Data Scientist Geospatial Analytics

Bunge

Chesterfield, MO • On-site

Full-time

Medical, Retirement, PTO

Posted 17 days ago


Bunge rating

7.1

Company rating: 7.1 out of 10

Based on 30 frontline employees who took The Breakroom Quiz

196th of 395 rated food and drinks producers


Job description

City : ChesterfieldState : Missouri (US-MO)Country : United States (US)Requisition Number : 46371
A Day In The Life:
Leveraging our inherent market intelligence is a critical component to Bunge's success, particularly in the dynamic agricultural markets. This the reason why Bunge has one of the large economic analysis teams in the industry. Our analysis team is comprised of over 50 analysts world-wide who gather, analyze, supply and demand and other pertinent information. The global analysts work closely with global traders to help market develop market theses that drive the company's trading and risk decisions. The team covers global grains, oilseeds, biofuels, ocean freight and livestock.
The Data Scientist, Geospatial Analytics will be a core contributor to Bunge's Global Economic Analysis team, applying data science, satellite imagery, advanced statistical modeling, and emerging generative AI techniques to generate valuable insights across global agricultural markets. This role will lead the development of scalable, satellite-based analytics that support global crop forecasting, supply chain intelligence, and commodity market analysis. The position focuses on integrating public Earth observation data with proprietary datasets and transforming them into actionable signals that enhance our understanding of crop conditions, acreage, yield potential, and global supply-demand dynamics.
What You'll Be Doing:
• Design, build and scale satellite-based analytics pipelines for real-time crop monitoring at globe scale;
• Analyze and integrate multi source datasets, including satellite imagery (Sentinel 1/2, Landsat, MODIS), weather and soil data, agricultural statistics, field level observations, and proprietary datasets
• Develop geospatial indicators such as NDVI anomalies, crop classifications, and yield signals to support trading and commercial decisions
• Leverage cloud infrastructure (e.g., Google Cloud Platform, AWS) for large scale geospatial data processing
• Utilize platforms and tools including Google Earth Engine, BigQuery, and Python based analytics pipelines
• Apply AI and machine learning techniques to imagery and time series data (e.g., classification, segmentation, feature extraction, and temporal modeling)
• Collaborate with economists, market analysts, data engineers, and business leaders to integrate geospatial insights into market views and fundamental analysis
• Monitor, evaluate, and continuously refine deployed models and analytics to ensure sustained accuracy and measurable business impact
• Clearly communicate complex analytical findings, model insights, and strategic recommendations to diverse audiences, including senior leadership and traders, to support informed decision making and global risk management
Skills/Experience Requirements:
• Master's degree or higher in Remote Sensing, Statistics, Computer Science, or a closely related quantitative field
• Minimum of 5 years of professional experience in remote sensing, geospatial analytics, or agricultural data science
• Advanced proficiency in Python (e.g., pandas, NumPy, scikit learn, statsmodels, TensorFlow, GeoPandas, rasterio)
• Strong SQL skills for data extraction, manipulation, and analysis across large datasets
• Solid understanding of geospatial data systems, projections, and large scale processing workflows
• Demonstrated ability to translate complex data and models into practical agricultural, commercial, or market insights
• Excellent communication and presentation skills, with the ability to explain complex analytical concepts clearly and concisely
• Highly detail oriented, proactive, and self motivated, with the ability to work both independently and collaboratively in a fast paced, global environment
Preferred Skills/Experience:
• Background in agriculture, crop modeling, or commodity research
• Experience working with radar data and vegetation indices
• Exposure to yield modeling, acreage estimation, or crop classification workflows
• Knowledge of agricultural commodity markets (e.g., grains, oilseeds, biofuels) and agronomic concepts
Bunge offers a variety of benefits including health and wellness plans, retirement contribution and paid vacation/holidays.
At Bunge (NYSE: BG), our purpose is to connect farmers to consumers to deliver essential food, feed and fuel to the world. As a premier agribusiness solutions provider, our team of ~34,000 dedicated employees partner with farmers across the globe to move agricultural commodities from where they're grown to where they're needed-in faster, smarter, and more efficient ways. We are a world leader in grain origination, storage, distribution, oilseed processing and refining, offering a broad portfolio of plant-based oils, fats, and proteins. We work alongside our customers at both ends of the value chain to deliver quality products and develop tailored, innovative solutions that address evolving consumer needs. With 200+ years of experience and presence in over 50 countries, we are committed to strengthening global food security, advancing sustainability, and helping communities prosper where we operate. Bunge has its registered office in Geneva, Switzerland and its corporate headquarters in St. Louis, Missouri. Learn more at Bunge.com.
Every day our people exemplify these values, which represent Bunge at its core:
We Are One Team - Collaborative, Respectful, Inclusive
We Lead The Way - Agile, Empowered, Innovative
We Do What's Right - Safety, Sustainability, With Integrity
If this sounds like you, join us! We value and invest in people who believe in our purpose and are excited to live it every day - people who are #ProudtoBeBunge

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