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Remote Geospatial Data Scientist Jobs (NOW HIRING)

For additional information on remote work at Penn State, seeNotice to Out of State Applicants. POSITION SPECIFICS We are looking for Research Data Scientist, to join our Geospatial Data Science team ...

Through survey research, geospatial analysis, and AI/ML, we are building scalable data ... Location Fully remote within the USA, with travel once or twice a year for retreats and conferences.

New

This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate is a practitioner who thinks first like an economist, real estate analyst, or quantitative urban ...

Civitech is a remote-first company hiring within our current footprint of 27 states (AL, AK, CA, CO ... Our rigorous approach to product design, testing, and data science leads to accurate assessments of ...

Software Engineer, Geospatial Data

Austin, TX · On-site +1

$113K - $136K/yr

Civitech is a remote-first company hiring within our current footprint of 27 states (AL, AK, CA, CO ... Our rigorous approach to product design, testing, and data science leads to accurate assessments of ...

Experience working with geospatial datasets and integrating AI/ML solutions into mission-critical ... Full remote flexibility. Working at SOSi All interested individuals will receive consideration and ...

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Remote Geospatial Data Scientist information

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$37.5K

$122.7K

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How much do remote geospatial data scientist jobs pay per year?

As of Jul 12, 2026, the average yearly pay for remote geospatial data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is the difference between Remote Geospatial Data Scientist vs Remote GIS Analyst?

AspectRemote Geospatial Data ScientistRemote GIS Analyst
Required CredentialsBachelor's/Master's in GIS, Geography, Data Science; experience with spatial analysisBachelor's in GIS, Geography, or related field; proficiency in GIS software
Work EnvironmentData analysis, modeling, programming, and spatial data interpretationMapping, data management, spatial data visualization
Employer & Industry UsageTech companies, environmental agencies, urban planningGovernment agencies, utilities, environmental firms
Common Search & ComparisonFocuses on data science and modelingFocuses on mapping and spatial data management

The Remote Geospatial Data Scientist primarily works on advanced spatial data analysis, modeling, and programming to extract insights from geospatial data. In contrast, the Remote GIS Analyst focuses on mapping, data management, and spatial visualization. Both roles require GIS knowledge but differ in their core responsibilities and skill sets.

How do Remote Geospatial Data Scientists typically collaborate with multidisciplinary teams across different time zones?

Remote Geospatial Data Scientists often work with professionals in fields like environmental science, urban planning, and software engineering, many of whom may be distributed globally. Effective collaboration relies on clear communication, regular virtual meetings, and the use of shared platforms for data, code, and project management. Flexible scheduling and asynchronous communication tools are key to coordinating across time zones, ensuring that all team members can contribute to project milestones efficiently. Building strong documentation and leveraging collaborative GIS and data platforms further help streamline workflows and maintain project momentum in a remote environment.

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

To thrive as a Remote Geospatial Data Scientist, you need a strong background in spatial analysis, statistics, and programming, typically supported by a degree in geography, computer science, or a related field. Experience with GIS software (such as ArcGIS or QGIS), remote sensing tools, and programming languages like Python or R is essential, along with familiarity with cloud-based data platforms. Strong problem-solving, self-motivation, and effective communication skills are vital for collaborating remotely and turning complex geospatial data into actionable insights. These skills enable professionals to efficiently interpret and analyze spatial data, deliver valuable solutions, and work effectively within distributed teams.

What is a Remote Geospatial Data Scientist?

A Remote Geospatial Data Scientist is a professional who analyzes and interprets spatial data, such as maps, satellite imagery, and GPS data, to solve problems or provide insights, all while working from a location outside of a traditional office. They use statistical, mathematical, and programming skills to process large geospatial datasets and often collaborate with teams virtually. Their work can support a variety of industries, including environmental monitoring, urban planning, and logistics, by providing actionable geographic insights. Remote geospatial data scientists commonly use tools like GIS software, Python, and machine learning frameworks. Communication and collaboration tools are also essential for effective remote work.
More about Remote Geospatial Data Scientist jobs
What cities are hiring for Remote Geospatial Data Scientist jobs? Cities with the most Remote Geospatial Data Scientist job openings:
What are the most commonly searched types of Geospatial Data Scientist jobs? The most popular types of Geospatial Data Scientist jobs are:
What states have the most Remote Geospatial Data Scientist jobs? States with the most job openings for Remote Geospatial Data Scientist jobs include:
Infographic showing various Remote Geospatial Data Scientist 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 $122,738 per year, or $59 per hour.
Data Scientist Geospatial Analytics

Data Scientist Geospatial Analytics

Bunge

Chesterfield, MO • On-site, Remote

Other

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 : Chesterfield State : 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 worldwide 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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