At Pula, we are radically restructuring agricultural insurance, using technology to insure the previously unbanked, uninsured, untapped market of 1.5 billion smallholders worldwide. We work in eight countries across Africa and Asia, and in 2017 alone, we facilitated crop and livestock insurance cover to 611,000 farmers in Kenya, Rwanda, Uganda, Nigeria, Ethiopia and Malawi.

Position Overview

As a Remote Sensing Data Analyst at Pula, you will turn satellite and geospatial data into reliable insights that support agricultural insurance products, yield estimation, and field operations. You will work closely with the Associate Manager and the data collection and field teams to validate remote sensing outputs against ground data, identify risks, and improve our analytical processes. We are looking for a motivated, data-driven person with strong documentation and project management skills who can move between strategic planning and hands-on analysis.

Responsibilities

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.

• 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.
• 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.
• 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.

• 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).
• 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.

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