Overview
Provide technical support for geospatial activities related to the use of Earth Observation (EO) data for agricultural statistics production and quality assurance. Focus on applying EO data to address data challenges in developing countries.
Tasks Summary
- Design, implement and validate EO based methodologies and indicators for crop area and yield, climate resilience, early warning systems and disaster impact assessments.
- Support the preprocessing and use of EO satellite images and time series.
- Apply geospatial data science and machine learning approaches.
- Design and support integrated data collection strategies combining EO, census, survey and in situ data.
- Establish end-to-end data quality assurance protocols.
- Foster data interoperability by linking datasets with geospatial data layers.
- Collaborate with and/or provide technical assistance to national technical counterparts.
- Contribute to the expansion of the EOSTAT and the Data Lab for statistical innovation initiatives.
- Contribute to capacity development activities tailored to national agricultural and statistical agencies.
- Support outreach activities to foster use of EO data access services and platforms.
- Translate geospatial analysis and trends into clear, actionable technical notes, policy briefs and programme recommendations.
- Support the dissemination of geospatial products.
Experience Requirements
- Minimum of 5 years of relevant experience in applying EO Data to agricultural monitoring, food and agriculture statistics, or evidence-based policy analysis with a demonstrable focus on developing country contexts.
- Experience in applying EO data to address real-world agricultural and data challenges in developing countries (e.g., for national crop area estimation, yield monitoring and forecasting, drought monitoring, disaster assessment and development of area frames).
- Experience conducting satellite image classification in heterogeneous agricultural landscapes typical of developing countries.
- Experience designing and managing complex agricultural data collection (e.g. the development of data collection and sampling protocols for in-situ data, their integration in agricultural surveys, and the design of digital data collection systems (e.g. ODK, SurveyCTO).
- Experience pre processing and analysing satellite image time series for agricultural monitoring and statistical applications.
- Experience performing in situ data cleaning, processing and analysis in combination with other datasets (survey, statistical and geospatial data) using appropriate statistical and spatial tools (e.g. R, SPSS, QGIS).
- Experience translating geospatial insights into clear policy advice, programme recommendations, or technical reports tailored for national government and development partners.
- Experience designing, validating and applying operational, context-appropriate EO-derived indicators for crop performance, productivity and climate impacts, taking into account local agronomic practices.
- Experience managing data integration, interoperability and quality assurance processes for geospatial applications.
- Experience supporting capacity development and institutional strengthening, including the preparation of training materials, facilitation of, and providing technical support to national institutions.
- Experience working with agricultural statistics and geospatial data produced by national agencies in developing countries.
- Demonstrated understanding of the structure, constraints and opportunities of agricultural statistics systems and farming systems in developing countries.
- Proven ability to collaborate effectively with both technical and non-technical national counterparts to integrate EO-based evidence into existing national monitoring, reporting and statistical production workflows.
- Proficiency in the use of spatial analysis tools (notably R and QGIS), including experience in addressing common data quality issues in developing regions.
- Ability to work independently, with minimum supervision.
Qualification Requirements
• Advanced university degree from an institution recognized by the International Association of Universities (IAU)/UNESCO in Environmental Science, Data Science, Informatics, Geography, Statistics or related fields; Consultants with a bachelor's degree need two additional years of relevant professional experience.
