FAO IS HIRING: Climate Data Analyst | Home-Based, Sri Lanka | 2026

FAO is recruiting a Climate Data Analyst for a home-based, 80-day Personal Services Agreement (PSA) assignment supporting its work on drought forecasting and anticipatory action in Sri Lanka. The position is based under the FAO Representation in Sri Lanka and is designed for professionals with experience in climate data analysis, statistical modelling, drought prediction, data science and artificial intelligence/machine learning.

The position was posted on 24 August 2026, with applications closing on 7 September 2026 at 11:59 PM according to the vacancy announcement.

Position: Climate Data Analyst
Organization: Food and Agriculture Organization of the United Nations (FAO)
Location: Home-Based, Sri Lanka
Contract: Personal Services Agreement (PSA)
Duration: 80 days, WAE
Salary: Not disclosed in the vacancy announcement
Job Reference: 2601818
Application deadline: 7 September 2026

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About FAO

The Food and Agriculture Organization of the United Nations (FAO) is a specialized agency of the United Nations working to combat hunger, improve food security and support sustainable agriculture and food systems.

FAO works with governments and partners across more than 130 countries. Its work covers agriculture, food security, nutrition, climate resilience, natural-resource management and sustainable development.

In Sri Lanka, FAO has worked since 1979, supporting national priorities related to agriculture, food security, nutrition and resilience.

This particular assignment forms part of FAO’s efforts to strengthen drought forecasting and anticipatory action. The objective is to improve the ability of institutions to predict drought conditions early enough to support decisions that can reduce agricultural and livelihood losses.

FAO Climate Data Analyst Opportunity Overview

The Climate Data Analyst will contribute to the development, testing and validation of data-driven approaches for drought forecasting and anticipatory action.

The role involves working with different types of environmental and climate datasets, developing statistical and machine-learning models, evaluating model performance and helping translate technical outputs into practical tools.

The successful candidate 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).

The analyst will also collaborate with the Drought Forecasting Expert, Anticipatory Action Coordinator and technical specialists working on early warning systems and anticipatory action.

What will the Climate Data Analyst do?

Key responsibilities include:

• Reviewing, cleaning, compiling and harmonizing climate and environmental datasets.
• Working with rainfall, vegetation, soil moisture, oceanic, forecast and historical drought data.
• Conducting exploratory data analysis to identify relationships and useful predictors.
• Performing correlation, lag-correlation, seasonality and cross-correlation analysis.
• Supporting predictor-importance analysis.
• Helping develop, train, optimize and validate ARIMAX models.
• Supporting drought forecasting using SPI-3 and selected predictors.
• Contributing to one-, two- and three-month drought forecasting.
• Assisting with Random Forest and Artificial Neural Network models.
• Supporting prediction of drought severity, intensity and probability of occurrence.
• Helping integrate model outputs into a web portal.
• Supporting automation of monthly model updates.
• Preparing methodology notes, validation reports and technical documentation.
• Contributing to user manuals, technical manuals and operational guidelines.

This makes the opportunity particularly relevant to professionals who enjoy combining climate science with data analytics, statistical modelling and machine learning.

Who Is This Opportunity Suitable For?

This FAO Climate Data Analyst position is most suitable for an experienced data professional who can work across both technical and applied areas.

It could be a strong match for professionals working as:

• Climate data analysts
• Data scientists
• Statistical analysts
• Meteorological data specialists
• Environmental data analysts
• Climate scientists
• Drought-modelling specialists
• Predictive-modelling specialists
• Agricultural data scientists
• Machine-learning professionals with climate applications

The position is not presented as an entry-level opportunity. FAO requires at least four years of relevant professional experience, so applicants should be able to demonstrate practical experience rather than relying only on academic qualifications.

The vacancy also has a specific geographical requirement: applicants must be nationals of Sri Lanka or residents of Sri Lanka with a valid work permit.

Salary and Benefits

How much does the FAO Climate Data Analyst earn?

FAO has not disclosed a salary or fee amount in the vacancy information provided.

Applicants should therefore avoid relying on unofficial salary estimates when evaluating this opportunity.

The assignment is a Personal Services Agreement (PSA) and has a duration of 80 days WAE (When Actually Employed).

Because the announcement does not provide a specific compensation figure or a detailed benefits package, applicants should not assume that the assignment carries the same remuneration structure as a regular FAO staff appointment.

Other features of the opportunity

The vacancy offers several professional advantages, including:

• Experience working with a UN specialized agency.
• Exposure to international climate and agricultural programmes.
• Experience in drought forecasting and anticipatory action.
• Opportunities to work with multidisciplinary technical experts.
• Practical exposure to statistical and machine-learning applications.
• Experience developing technical documentation and operational tools.
• Home-based working arrangement as specified in the vacancy.

These can be particularly valuable for professionals seeking to build careers in climate resilience, disaster risk reduction, food security, early warning systems and international development.

Required Qualifications Explained

FAO requires a university degree in one of several relevant disciplines.

The accepted fields include:

• Statistics
• Data Science
• Mathematics
• Climate Science
• Meteorology
• Environmental Science
• A related discipline with sufficient background in climate/weather data analysis and drought modelling

Why the academic background matters

This is a technically focused position. Applicants need more than general data-analysis knowledge because the assignment involves climate datasets, drought indicators, forecasting models and predictive analytics.

For example, someone with a degree in data science should be able to demonstrate relevant experience applying analytical techniques to environmental or climate-related problems.

Similarly, a meteorologist or climate scientist would benefit from demonstrating strong statistical and programming capabilities.

The strongest applications are likely to connect the applicant’s academic background directly to the technical requirements of the assignment.

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Required Experience

FAO requires at least four years of relevant professional experience in the public or private sector.

Relevant experience may include:

• Statistical analysis
• Climate data analysis
• Drought modelling
• Predictive modelling
• Data science
• Environmental data analysis
• Statistical programming
• Machine learning applied to climate or environmental datasets

Applicants should make their experience measurable and specific.

Instead of simply writing:

“Experienced in data analysis.”

A stronger CV description would explain the type of datasets handled, analytical methods used, software applied and the purpose or outcome of the analysis.

Technical Skills FAO Is Looking For

The vacancy identifies several important technical capabilities.

Programming and statistical tools

Familiarity with tools such as:

• Python
• R
• SAS
• SQL
• Relevant AI/ML tools

is requested.

Applicants should not simply list these technologies in a skills section. Where possible, they should demonstrate how they have used them in previous projects.

Statistical and predictive modelling

FAO is looking for candidates with technical skills in areas such as:

• Statistical analysis
• Data visualization
• Data modelling
• Data mining
• Predictive modelling
• Spatial visualization
• Artificial intelligence
• Machine learning
• Statistical advisory support

Experience with climate or environmental datasets can be particularly relevant because of the technical focus of this assignment.

Reporting and communication

The position also involves preparing reports and presenting information visually.

This means the successful candidate needs to communicate technical findings clearly rather than only performing analytical work behind the scenes.

Language Requirements

The vacancy requires working knowledge of English and Sinhala and/or Tamil.

The language requirement is important because the role supports work in Sri Lanka and involves collaboration with national institutions.

FAO also states that only language proficiency certificates from UN-accredited external providers and/or FAO language examinations will be accepted as proof of language level where such proof is required in the application.

Applicants should therefore provide accurate information about their language abilities.

How Competitive Is the FAO Climate Data Analyst Opportunity?

This is likely to be a technically competitive assignment because it combines several specialized areas rather than requiring general administrative or data-entry skills.

Applicants need to demonstrate a combination of:

1. Relevant academic training.
2. At least four years of professional experience.
3. Climate or weather data expertise.
4. Statistical analysis capability.
5. Programming knowledge.
6. Predictive modelling experience.
7. AI/machine-learning familiarity.
8. Understanding of drought or environmental applications.
9. Strong communication and documentation skills.
10. Eligibility to work in Sri Lanka under the stated nationality/residency requirement.

The vacancy does not provide an applicant-to-position ratio or other competition statistics, so no reliable numerical estimate of competitiveness can be given.

A candidate who meets only the general data-science requirements but lacks climate, weather or drought-modelling experience may find it harder to demonstrate a close match to the assignment.

How to Prepare Your CV for the FAO Application

Your CV should make it easy for the recruiter to identify your match with the vacancy.

1. Put your most relevant experience first

Prioritize experience involving:

• Climate datasets
• Drought analysis
• Forecasting
• Statistical modelling
• Machine learning
• Environmental analytics
• Data science
• Early warning systems

2. Show your programming experience

Mention specific programming languages and tools you have actually used.

For example:

Python: predictive modelling, data cleaning and machine-learning workflows.

R: statistical analysis, time-series modelling and visualization.

Only include skills you can genuinely demonstrate.

3. Highlight modelling projects

If you have worked on forecasting or predictive models, describe:

• The problem you were solving.
• The dataset used.
• The modelling technique.
• The tools or programming language.
• How the model was evaluated.
• The practical purpose of the results.

4. Quantify achievements where possible

Instead of saying:

“Cleaned climate datasets.”

Consider explaining the scale or outcome, if accurate:

“Cleaned and harmonized multiple historical climate datasets to support predictive modelling and drought-risk analysis.”

Do not add numbers simply to make the CV appear stronger.

5. Include relevant academic work

If your professional experience is strong but your CV does not clearly demonstrate drought or climate modelling, relevant master’s research, university projects, publications or technical projects can help establish your technical background.

Common Application Mistakes to Avoid

Applying without meeting the eligibility requirements

The Sri Lanka nationality/residency requirement is important. Applicants should verify that they meet it before investing time in the application.

Submitting a generic data-science CV

A general data-science CV may not adequately demonstrate experience with climate, weather or drought datasets.

Tailor your CV toward the technical focus of this assignment.

Listing software without evidence

Writing “Python, R, SQL, AI” without showing how you have used these tools gives recruiters little evidence of practical competence.

Ignoring the four-year experience requirement

The vacancy specifically requests at least four years of relevant professional experience.

Applicants should clearly show the dates, employers, responsibilities and relevance of their professional experience.

Submitting an incomplete application

FAO states that incomplete applications will not be considered.

Candidates should ensure their online profile contains accurate information about employment history, academic qualifications and language skills.

Waiting until the final day

FAO encourages candidates to submit applications well before the deadline. Technical problems or incomplete information can create unnecessary risks when applying close to the closing time.

Career Paths After a Climate Data Analyst Role

Experience from this assignment could support future careers in several related fields.

Professionals may eventually pursue roles such as:

• Climate Data Scientist
• Climate Risk Analyst
• Drought Modelling Specialist
• Environmental Data Scientist
• Disaster Risk Reduction Specialist
• Early Warning Systems Analyst
• Climate Adaptation Specialist
• Agricultural Data Scientist
• Machine Learning Specialist
• Climate Resilience Consultant
• Monitoring, Evaluation and Learning Specialist with climate-data expertise

The combination of data science, climate analytics and international development experience can also be useful for careers with UN agencies, development organizations, research institutions, governments and climate-focused organizations.

Similar Opportunities to Consider

Professionals interested in this vacancy can also look for opportunities involving:

• Climate data science
• Agricultural data analysis
• Drought monitoring
• Climate-risk modelling
• Early warning systems
• Disaster preparedness
• Food security
• Environmental modelling
• Climate adaptation
• Machine learning for environmental applications
• Anticipatory action

Within international development, candidates should monitor technical positions with organizations working in food security, agriculture, climate resilience and disaster-risk reduction.

Official Application Information

The FAO Climate Data Analyst vacancy is listed under job reference 2601818.

The vacancy was posted on 24 August 2026 and is scheduled to close on 7 September 2026 at 11:59 PM. The announcement notes that the displayed closing time can be affected by the applicant’s personal device settings.

Applications must be submitted through the official FAO recruitment portal. FAO states that only applications received through its recruitment portal will be considered.

Candidates should complete their online profile, provide employment and academic information, include language skills and attach a letter of motivation as requested in the vacancy.

FAO also states that it does not charge a fee at any stage of recruitment, including applications, interviews or processing.

For recruitment-related assistance, candidates can use FAO’s official support service:

Final Thoughts

The FAO Climate Data Analyst 2026 opportunity is a specialized assignment for professionals who can combine climate knowledge with advanced data analysis and predictive modelling.

The strongest candidates will not simply demonstrate that they can work with data. They will show how their experience in climate/weather data, drought modelling, statistical analysis, programming, forecasting and machine learning can contribute to anticipatory action and improved drought preparedness.

Because the vacancy is restricted to Sri Lankan nationals or residents with a valid work permit, eligible professionals should carefully review the requirements before applying.

The salary is not disclosed in the vacancy announcement, so applicants should rely on the official FAO recruitment information rather than unofficial compensation figures.

For eligible candidates with the required technical background, this assignment offers an opportunity to contribute to an important climate-resilience initiative while gaining experience connected to FAO’s work on agriculture, food security, drought forecasting and anticipatory action.