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Data Scientist Geospatial AnalyticsBunge Iberica SA • Chesterfield, Missouri, United States
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Data Scientist Geospatial Analytics

Bunge Iberica SA
  • US
    Chesterfield, Missouri, United States
  • US
    Chesterfield, Missouri, United States
Jetzt Bewerben

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Data Scientist Geospatial Analytics Location:
Chesterfield, MO -Missouri, US, 63017
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 is the reason why Bunge has one of the largest 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 mult-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.
Benefits Bunge offers a variety of benefits including health and wellness plans, retirement contribution and paid vacation/holidays.
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  • Chesterfield, Missouri, United States

Sprachkenntnisse

  • English
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