Specialist in Agrometeorology, Early Warning, and Artificial Intelligence/Machine Learning

Overview

The role focuses on strengthening climate-resilient agriculture by integrating agrometeorology, early warning systems, and Artificial Intelligence/Machine Learning. The purpose is to develop data-driven solutions for improved preparedness, reduced agricultural losses, and enhanced climate resilience.

Tasks Summary

• Translate climate and weather forecasts into agricultural risk insights for crops, livestock, and fisheries.
• Develop agro-advisories and decision-support tools for farmers and policy makers.
• Design and strengthen early warning systems integrating climate, hydrological, and agricultural data.
• Define risk thresholds and trigger mechanisms for anticipatory action, and support strengthening of their monitoring systems, including automation of these.
• Ensure last-mile communication of warnings through user-friendly channels and formats.
• Train extension officers and communities on interpreting early warnings and applying agro-advisories.
• Contribute to technical reports on best practices, approaches and policies to increase the development of advanced climate services for agriculture.
• Apply AI/ML models for predictive analytics and strengthen early warning systems in data-poor areas.
• Integrate multiple data sources (remote sensing, IoT, farmer registries, climate models) into ML pipelines.
• Test and validate models for accuracy, scalability, and operational use in decision-making.
• Build capacity of national meteorological agencies, agricultural ministries, and local institutions on agrometeorology and AI-driven forecasting.
• Lead applied research and pilot initiatives linking agrometeorology, anticipatory action, and AI/ML innovations such as agent-based advisors and digital twins.
• Collaborate with governments, universities, research centers, and technology providers and users (e.g. insurance providers) on model development and validation.
• Pilot and scale innovative approaches such as mobile-based agro-advisory apps and automatization of anticipatory action triggers.
• Contribute to the formulation of GEF, GCF, and Adaptation Fund (AF) concept notes and full funding proposals.
• Perform other related duties as required.

Experience Requirements

• 1 year of relevant experience for Category C, 5 years of relevant experience for Category B, and 10 years of relevant experience for Category A in analytical studies, and/or in planning, design, supervision of meteorology and agrometeorology projects and programmes, including in developing countries and/or countries in transition.
• Extent and relevance of experience in designing and implementing agrometeorological and early warning systems for agriculture and food security.
• Extent and relevance of experience in applying AI/ML techniques to climate and agricultural datasets, including model development, testing, and validation.
• Extent and relevance of experience in conducting climate risk and vulnerability assessments and translating forecasts into actionable agro-advisories for farmers, governments, and development partners.
• Extent and relevance of experience in developing digital tools, platforms, or services that integrate climate, remote sensing, and agricultural data to support anticipatory action and disaster risk reduction.
• Extent and relevance of experience in preparing technical studies, knowledge products, or operational guidelines on agrometeorology, early warning, and AI/ML applications in agriculture.
• Extent and relevance of experience in strengthening institutional and community capacities to use climate information, early warning, and AI/ML-driven decision-support systems.
• Demonstrated ability to work with government agencies, national meteorological and hydrological services, agricultural institutions, and private sector partners to co-develop and apply forecasting and early warning solutions.
• Relevance of experience in developing countries and/or in Asia and the Pacific, particularly in applying agrometeorology and AI/ML to support climate resilience in agriculture.

Qualification Requirements

• Advanced university degree from an institution recognized by the International Association of Universities (IAU)/UNESCO in agrometeorology, climatology, meteorology, hydrology, data science or artificial intelligence. Consultants with a bachelor's degree need two additional years of relevant professional experience.
• University degree from an institution recognized by the International Association of Universities (IAU)/UNESCO in agrometeorology, climatology, meteorology, hydrology, data science or artificial intelligence.

Other Details

Languages Required: • Working knowledge (level C) of English.

Languages Preferred: • Working knowledge of Chinese, French, Spanish, Arabic or Russian seen as an asset, but not mandatory.

Contract Duration: Up to 11 months

Work Modality: Home-Based

Remuneration: