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Remote Agriculture Data Science Jobs (NOW HIRING)

Expert Professionals -- AI & Data Science Type: Contract Compensation: $70-$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to close ...

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Remote Agriculture Data Science information

What is remote agriculture data science?

Remote agriculture data science involves analyzing and interpreting agricultural data from a distance, often using digital tools and remote sensing technologies. Professionals in this field leverage data collected from satellites, drones, sensors, and farm management systems to provide insights that help optimize crop yields, monitor soil health, and improve resource management. Working remotely, these data scientists use statistical models, machine learning, and geographic information systems (GIS) to assist farmers and agribusinesses in making data-driven decisions. The role can include tasks such as predictive analytics, data visualization, and building decision support tools, all performed from a location outside the traditional farm or office setting.

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

To thrive as a Remote Agriculture Data Scientist, you need a solid background in statistics, machine learning, agronomy, and data analysis, typically supported by a degree in data science, agriculture, or a related field. Proficiency with analytical tools like Python, R, GIS platforms, and cloud-based data management systems is commonly required. Strong problem-solving, communication, and self-motivation skills are essential for collaborating with remote teams and stakeholders. These skills enable effective interpretation of agricultural data, driving informed decisions and innovation in the sector.

How do remote agriculture data scientists typically collaborate with on-site agronomists and farm teams?

Remote agriculture data scientists often work closely with on-site agronomists and farm teams through regular virtual meetings, shared data platforms, and cloud-based tools. Communication is key; they may interpret sensor or satellite data and translate insights into actionable recommendations, which are then validated or implemented by on-the-ground staff. Building strong relationships and maintaining clear channels for feedback is essential to ensure that data-driven solutions align with real-world agricultural conditions. This collaborative approach helps bridge the gap between advanced analytics and practical farm management.
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What are the most commonly searched types of Agriculture Data Science jobs? The most popular types of Agriculture Data Science jobs are:
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Data Scientist Geospatial Analytics

Data Scientist Geospatial Analytics

Bunge

Chesterfield, MO • On-site, Remote

Other

Medical, Retirement, PTO

Posted 7 days ago


Bunge rating

7.1

Company rating: 7.1 out of 10

Based on 30 frontline employees who took The Breakroom Quiz

198th of 389 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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