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Tech Stack
Tools & technologiesCloudPythonRemote SensingSQL
About the role
Key responsibilities & impact- Acquire, process, and analyze satellite imagery including Sentinel, Landsat, MODIS, and Planet, plus vegetation indices, rainfall, and soil moisture products
- Develop and maintain workflows for crop type mapping, crop condition monitoring, yield estimation, and loss assessment
- Validate remote sensing outputs using ground-truth data from crop cutting experiments and field surveys
- Work with field boundaries, GPS points, and administrative layers in GIS tools
- Support spatial sampling design for crop cutting experiments and surveys
- Run data quality checks on remote sensing and field-collected data following SOPs
- Identify gaps in quality-check SOPs and recommend improvements
- Configure surveys and allocate field agents on the in-house data collection tool
- Assist in survey creation and participate in crop cutting experiment and survey work as required
- Identify project risks and issues and propose practical solutions
- Determine appropriate methods for data analysis, quality checks, and operations assessment
- Document findings, prepare reports and maps, and make recommendations
- Develop and evaluate processes and procedures to improve project operations
- Draft training materials, protocols, and technical documentation
- Train field staff on new systems and processes
- Provide the manager with regular daily, weekly, and ad-hoc updates
Requirements
What you’ll need- Bachelor’s degree in Statistics, Economics, Agricultural Economics, Agribusiness Management, Geography/Geoinformatics, Environmental Science, Information Systems, or a related field
- Minimum of 2 years of experience in data analysis, preferably in a fast-paced NGO or agri-tech environment
- Demonstrated experience working with satellite imagery or geospatial data
- Proficiency in Python and R, including geospatial libraries such as rasterio, geopandas, GDAL, sf, and terra
- Experience with GIS software such as QGIS or ArcGIS and cloud platforms such as Google Earth Engine
- Proficiency in data visualization tools such as Power BI or similar
- Knowledge of SQL
- Familiarity with mobile data collection tools such as CommCare, KoboToolbox, or SurveyCTO
- Knowledge of statistical methods for validation, sampling, and model evaluation
- Ability to explain complex technical information through clear writing and strong verbal communication
- Ability to turn technical data into presentations and maps for diverse audiences
- Strong collaboration skills and team spirit
- Self-driven, able to work independently with minimal supervision
- Ability to manage multiple tasks, prioritize, and meet deadlines
- Experience with agricultural insurance, index-based products, or smallholder farming contexts is nice to have
- Experience with SAR data, weather data, or cloud-based geospatial pipelines is nice to have
Benefits
Comp & perks- No specific benefits or compensation extras stated