Data Analyst-Remote Sensing

Remote sensing and geospatial analysis

• Acquire, process, and analyze satellite imagery (e.g., Sentinel, Landsat, MODIS, Planet) and derived products such as vegetation indices (NDVI, EVI), rainfall, and soil moisture.
• 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 (CCEs) and field surveys.
• Work with geospatial data, including field boundaries, GPS points, and administrative layers, in GIS tools.
• Support sampling design, including spatial sampling, for CCEs and surveys.

Data quality and field operations

• Run data quality checks on remote sensing and field-collected data following SOPs.
• Identify gaps in current 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 CCE and survey work as required

Analysis, reporting, and improvement

• Use data analytics and project knowledge to identify risks and issues within projects, and propose practical solutions.
• Determine appropriate methods for data analysis, quality checks, and operations assessment.
• Document findings, prepare reports and maps, and make recommendations based on your analysis.
• Develop new processes and procedures to improve project operations, and evaluate their effectiveness once implemented.
• Draft training materials, protocols, and technical documentation, and train field staff on new systems and processes.
• Keep the manager informed through regular daily, weekly, and ad-hoc updates.
• Demonstrate honesty and transparency, and communicate directly and openly, giving feedback constructively.

Requirements

Education and experience

• 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.

Technical skills

• Proficiency in Python and R (required), including geospatial libraries (e.g., rasterio, geopandas, GDAL, sf, terra).
• Experience with GIS software (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 (required).
• Familiarity with mobile data collection tools such as CommCare, KoboToolbox, or SurveyCTO.
• Knowledge of statistical methods for validation, sampling, and model evaluation (preferred: machine learning for classification or regression).

Skills and competencies

• 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.

Nice to have

• Experience with agricultural insurance, index-based products, or smallholder farming contexts.
• Experience with SAR data, weather data, or cloud-based geospatial pipelines.