National Crop And Statistical Modelling Expert

IMPORTANT NOTICE: Please note that Closure Date and Time displayed above are based on date and time settings of your personal device FAO is committed to achieving workforce diversity in terms of gender, nationality, background and culture Qualified female applicants, qualified nationals of non-and under-represented Members and person with disabilities are encouraged to apply Everyone who works for FAO is required to adhere to the highest standards of integrity and professional conduct, and to uphold FAO's values FAO, as a Specialized Agency of the United Nations, has a zero-tolerance policy for conduct that is incompatible with its status, objectives and mandate, including sexual exploitation and abuse, sexual harassment, abuse of authority and discrimination All selected candidates will undergo rigorous reference and background checks All applications will be treated with the strictest confidentiality Organizational Setting The Food and Agriculture Organization (FAO) is a specialized agency of the United Nations that leads international efforts to defeat hunger.
FAO's goal is to achieve food security for all and ensure that people have regular access to enough high-quality food to lead active, healthy lives.
With members - countries and the European Union, FAO works in over countries worldwide and has started working in Sri Lanka since with its Representation (Country Office) opened in Colombo.
The FAO contributes to the achievement of the Agenda through its Strategic Framework by supporting the transformation to more efficient, inclusive, resilient and sustainable agri-food systems, and through four Betters (Better production, Better nutrition, a Better environment and a Better life) - leaving no one behind.
Reporting Lines The National Crop and Statistical Modelling Expert will work under the overall supervision of the FAO Representative for Sri Lanka and the Maldives, the direct supervision of the Assistant FAO Representative (Programmes), and technical guidance of the Lead Technical Officer of the project.
The incumbent will work under the supervision and leadership of the Socio Economic and Planning Centre (SEPC), in coordination with the TCP Operations Specialist, Digital Agriculture Implementation Specialist, relevant government institutions and technical stakeholders to support the effective implementation, coordination, validation, and institutionalization of the CROPIX-AI initiative.
Technical Focus The objective of this assignment is to provide technical expertise for the design, development, calibration, validation, and operationalization of paddy and maize crop growth, yield and production forecasting models, including agricultural data harmonization, statistical and AI-based modelling, crop damage assessment, forecast adjustment, and capacity building, supporting the integration and continuous improvement of accurate, timely and spatially disaggregated forecasts within CROPIX-AI under TCP/SRL/.
Tasks and responsibilities The expert will provide technical support for the tasks below under SEPC's supervision and leadership, following an agreed workplan and methodologies approved by SEPC in consultation with the FAO Lead Technical Officer.
I. Agricultural Data Assessment and Modelling Dataset Development • Review and assess paddy and maize datasets available from DOA, DCS, DAD, DoM, Mahaweli Authority, NRMC and other relevant institutions for their suitability for model development and forecasting.
• Assess data completeness, consistency, temporal and spatial coverage, definitions, classifications, reporting frequencies and methodological differences across datasets.
• Identify and address missing values, outliers, inconsistencies, structural breaks and other data-quality issues that may affect model performance.
• Support the development and maintenance of modelling-ready datasets covering historical production, cultivated area, yield, weather, soil, fertilizer use, irrigation, crop varieties, crop management practices, and other relevant variables.
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• Harmonize crop classifications, geographic references, agro-ecological zones, cropping seasons and key modelling variables.
• Support the development and maintenance of a data dictionary and metadata framework for datasets used in model development, calibration, and validation.
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• Ensure datasets used for model training, testing and validation are appropriately documented, traceable and version-controlled.
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Crop Model Design and Development • Assist with the technical and operational tasks involved in designing and developing paddy and maize crop growth and yield forecasting models suited to Sri Lankan agro-ecological zones, climatic conditions, cropping seasons, and production systems, under the guidance of the supervisor.
Support the development of model architectures, parameters, variables, and forecasting methodologies for estimating crop growth, yield, and to