<hr> <table style="height:45.9972px;width:100%;border-style:solid;background-color:#043c5a;border-color:#aaa5a5" border="1"> <tbody> <tr style="height:45.9972px"> <td style="width:25%;height:42.9972px;text-align:center">City : Chesterfield </td> <td style="width:25%;height:42.9972px;text-align:center">State : Missouri (US-MO) </td> <td style="width:25%;height:42.9972px;text-align:center">Country : United States (US) </td> <td style="width:25%;height:42.9972px;text-align:center">Requisition Number : 46371 </td> </tr> </tbody> </table> 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.<hr> 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 <hr>

Data Scientist Geospatial Analytics (Chesterfield, MO -Missouri, US, 63017) @ Bunge

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