Data Scientist Geospatial Analytics

Key Responsibilities

• 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

Required Skills & Experience

• 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.

Pay

N/A

Schedule

N/A

Qualifications

N/A

Skills

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Benefits

Bunge offers a variety of benefits including health and wellness plans, retirement contribution, and paid vacation/holidays.

Pay

N/A

Schedule

N/A

Qualifications

N/A

Skills

N/A