National Crop and Statistical Modelling Expert
Organizational Context
The Food and Agriculture Organization (FAO) is a United Nations specialized agency dedicated to eradicating hunger and promoting food security globally. Operating in over 130 countries since 1979, FAO Sri Lanka supports the transformation of agri-food systems towards greater efficiency, inclusivity, resilience, and sustainability. Its work aligns with the 2030 Agenda, focusing on 'Better Production, Better Nutrition, a Better Environment, and a Better Life,' ensuring no one is left behind.
Job Purpose
This role provides critical technical expertise for the design, development, calibration, validation, and operationalization of crop growth, yield, and production forecasting models for paddy and maize. It involves harmonizing agricultural data, applying statistical and AI-based modelling techniques, assessing crop damage, adjusting forecasts, and building capacity. The ultimate goal is to enhance the accuracy, timeliness, and spatial disaggregation of forecasts within the CROPIX-AI system, contributing to improved agricultural planning and response in Sri Lanka under TCP/SRL/4107.
Responsibilities
The expert will provide technical support in assessing and developing agricultural datasets, ensuring data quality, completeness, and harmonization for paddy and maize modelling. Responsibilities include designing and developing crop growth and yield forecasting models using statistical, AI, and hybrid approaches, tailored to Sri Lankan conditions. This involves integrating key variables like weather, soil, and management practices, and developing growth-stage-specific models. The role also entails calibrating and validating models using diverse data sources, optimizing performance, and assessing crop damage and climate risks. Furthermore, the expert will integrate multi-source data into forecasting workflows, establish data pipelines, monitor forecast performance, and engage with stakeholders for validation and capacity building. Comprehensive technical documentation and reporting on model development, validation, and improvements are also key duties.
Work Experience
A minimum of 8 years of relevant professional experience is required, specifically in areas such as crop modelling, agricultural forecasting, or agricultural statistics. This experience should complement an advanced university degree in a related scientific or technical field. The candidate must also possess working knowledge of English, Sinhala, and/or Tamil, and be a national of Sri Lanka or hold a valid work permit.
Skills
Key skills include demonstrated experience in designing, calibrating, and validating crop forecasting models (statistical, process-based, AI/ML, remote-sensing, or hybrid), particularly for staple crops. Proven ability to integrate and harmonize multi-source agricultural, climatic, and statistical datasets, including data quality assessment and management of large datasets, is crucial. Proficiency in statistical and machine-learning software/programming languages like R and Python, along with experience in crop simulation platforms and model performance evaluation, is essential. Strong results focus, teamwork, communication, relationship building, and knowledge sharing capabilities are also required.