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The Climate Data Analyst will support the development, testing, and validation of trigger methodologies and impact-based forecasting for drought anticipatory action in Sri Lanka. This includes cleaning climate datasets, developing predictive models, and facilitating the integration of these outputs into national decision-making systems.
Organizational Setting and Context
The Food and Agriculture Organization of the United Nations (FAO) is a specialized UN agency mandated to lead global efforts to eradicate hunger and achieve food security for all. Its core objective is to ensure sustained access to sufficient, safe and nutritious food that enables people to lead active and healthy lives. With 195 members—194 countries and the European Union—FAO operates in over 130 countries. In Sri Lanka, FAO has been engaged since 1979, with its country representation established in Colombo to support national development priorities in agriculture, food security, nutrition and resilience.
FAO contributes to the realization of the 2030 Agenda for Sustainable Development through its Strategic Framework, which focuses on transforming agri-food systems to be more efficient, inclusive, resilient and sustainable. This transformation is operationalized through the “Four Betters”: Better Production, Better Nutrition, a Better Environment and a Better Life, while ensuring that no one is left behind.
Since 2025, FAO Sri Lanka has initiated drought-related anticipatory action. While Sri Lanka currently undertakes drought monitoring based on observed conditions, there is a critical gap in operational drought prediction. Effective anticipatory action requires reliable, science-based drought forecasting with adequate lead time to trigger predefined actions that reduce agricultural and livelihood losses.
Under the Technical Cooperation Programme (TCP/SRL/4102), a Drought Forecasting Expert has been recruited to support the Government of Sri Lanka—particularly the Department of Agriculture, Department of Meteorology and Disaster Management Centre—to develop and institutionalize an advanced drought prediction system through strengthened technical collaboration, data integration and capacity building.
Key activities include:
• Activity 1: Strengthen drought prediction capabilities and develop context-specific drought indices.
• Activity 2: Operationalize the use of drought forecasts within agricultural decision systems.
• Activity 3: Facilitate the development and implementation of anticipatory action triggers and SOPs.
• Activity 4: Enhance national capacity and ensure long-term institutional sustainability.
Reporting Lines
The Climate Data Analyst will work under the overall supervision of the FAO Representative for Sri Lanka and the Maldives and the direct supervision of the Assistant FAO Representative (Programmes). Working closely with the Drought Forecasting Expert and Anticipatory Action Coordinator. In addition, the incumbent will work closely with FAO RAP Disaster Resilience and Inclusion team specifically the Early Warning Systems Expert and Regional Anticipatory Action Specialist.
Technical Focus
The objective of the assignment is to support FAO in developing, testing, and validating trigger methodologies and impact-based forecasting approaches for Anticipatory Action in Sri Lanka. The role will further support the standardization of related processes and contribute to the development of materials, tools, and knowledge products that facilitate the mainstreaming, coordination, and dissemination of anticipatory action approaches.
Tasks and responsibilities
The Climate Data Analyst will,
• Support FAO in reviewing, compiling, cleaning, and harmonizing relevant rainfall, climate, vegetation, soil moisture, oceanic, forecast, and historical drought datasets to ensure data quality, consistency, and readiness for analysis.
• Provide technical support to FAO in conducting exploratory data analysis, including correlation analysis, lag correlation analysis, seasonality assessment, cross-correlation analysis, and predictor importance analysis, to identify suitable variables for drought prediction.
• Support FAO in developing, training, optimizing, and validating ARIMAX models using SPI-3 and selected predictors to generate one-month, two-month, and three-month drought forecasts.
• Assist FAO in developing and comparing AI/ML models, including Random Forest and Artificial Neural Network models, to predict SPI-3, drought severity, drought intensity, and the probability of drought occurrence.
• Facilitate FAO’s efforts to integrate model outputs into the web portal, support the automation of monthly model updates, and prepare comprehensive documentation, including methodology notes, validation reports, source code documentation, user manuals, technical manuals, and operational guidelines.
CANDIDATES WILL BE ASSESSED AGAINST THE FOLLOWING
Minimum Requirements
• University degree in Statistics, Data Science, Mathematics, Climate Science, Meteorology, Environmental Science, or a related field, with sufficient background in climate/weather data analysis and drought modelling.
• At least 4 years of relevant professional experience in the public or private sector, preferably in statistical analysis, climate data analysis, drought modelling, predictive modelling, or data science.
• Working knowledge of English and Sinhala and/or Tamil.
• National of Sri Lanka or resident of the country with a valid work permit.
FAO Core Competencies
• Results Focus
• Teamwork
• Communication
• Building Effective Relationships
• Knowledge Sharing and Continuous Improvement
Technical/Functional Skills
• Familiarity with programming and statistical software/tools, such as R, Python, SAS, SQL, and relevant AI/ML tools.
• Demonstrated technical skills in statistical analysis, data visualization, data modelling, data mining, predictive modelling, spatial visualization, artificial intelligence/machine learning, and statistical advisory support.
• Good command of computer skills (MS Word, Excel, Powerpoint, Internet);
• Understanding of FAO policies and programme is considered a strong asset.
• Experience working with preparing reports and presenting information visually.
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