Data Scientist

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FAO seeks gender, geographical and linguistic diversity in its staff and international consultants in order to best serve FAO Members in all regions.

• 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
• FAO staff are subject to the authority of the Director-General, who may assign them to any of the activities or offices of the Organization.

Organizational Setting

Under UNJP/ALB/022/JP, FAO Albania leads efforts with the International Labour Organisation (ILO) and the International Telecommunication Union (ITU) to support the sustainable digital transformation of Albania’s agriculture and rural areas with an ambitious 3-years joint programme entitled “Digital Agriculture and Rural Transformation (DART)” as part of the SDG Fund – Digital Transformation Window call.

DART aims to increase agriculture productivity, advance socio-economic growth, and enhance rural livelihoods in Albania by 2027. It harnesses the potential of digitalization to transform the agri-food sector from national level to underserved rural areas in Albania delivering on three components\: 1) the formulation of Albania’s National Digital Agriculture Strategy and Action Plan (led by FAO, with support from ITU) 2) the farmer-centric design and delivery of digital services via the recently launched national Farmers’ Portal (Portali i Fermerit) (led by FAO) 3) the development of digital capacities among national public workers, TVET schools and centres; smallholder farmers and other vulnerable groups in rural areas (led by ILO).

The deliverable under Component 2 is the enhancement of the Albania Farmers’ Portal, which is meant to become a one-stop-shop dynamic tool, delivering near real-time site and crop-specific information to smallholders, while connecting farmers to advisories and state-of-the-art agronomic practices, in parallel of providing meaningful insights of the national agricultural ecosystem to the government. To achieve this, FAO Albania is seeking a technically strong and analytically driven Data Scientist to join the team developing this upgraded platform. The ideal candidate will bring a solid foundation in statistics, strong coding proficiency Python, and the ability to work with machine learning (ML) and large language models (LLM). Experience with geospatial data is a plus—but not required—as mentorship will be provided.

This position offers a National Personal Service Agreement (PSA.NAT) contract for an initial 230 days (equivalent to 11 months). A break from duty of at least 30 consecutive days is mandatory within any twelve-month period after which the contract is renewable upon satisfactory performance and funds availability.

Only persons holding citizenship and/or valid residence permit in Albania are eligible to apply.

The incumbent shall be based in Tirana

Reporting Lines

Under the overall supervision and technical leadership of the FAO Senior Technical Advisor on Digital Agriculture, in close coordination with the Back-End and Front-End Developers, the service designer, and relevant national partners, the Data Scientist shall undertake the tasks and responsibilities outlined below.

Technical Focus

In close collaboration with the technical team members, the Data Scientist will support the development and evaluation of analytics pipelines for field-level and national-scale agricultural monitoring, including modelling exercises using machine learning algorithms for real-world agronomic relevant metrics and application of LLM to deliver meaningful agronomic advice. In details, the work may specifically include, the retrieval of biophysical and biochemical vegetation traits and indices (e.g. NDVI, LAI, fCover) for modelling purpose, benchmarking field boundary detection algorithms for further deployment, and customization of LLMs to deploy a farmer-facing chatbot. The role will balance research-oriented experimentation with practical delivery of code and outputs.

Tasks and responsibilities

1. EO Data Processing and Predictive Modeling
• Explore EO (Earth Observation) open-source tools and products (e.g. GEE, Sen4Stat) for retrieval of meaningful agronomic metrics.
• Design, test, and apply ML models for vegetation monitoring using satellite imagery and weather data (e.g. clustering, temporal smoothing, weather anomalies) to create agricultural related metrics.
• Benchmark and assist in the automation of field-boundary detection algorithms.
• Assist in the evaluation of model accuracy and operational suitability of field and national-level EO products aggregation.
• Ensure reproducibility and clear documentation of statistical workflows.
• Collaborate with the Back-End Developer to validate and optimize EO-derived indicators used in the Farmers’ Portal.
2. LLM and AI Applications
• Test and customize open source LLM (or in-house models) for the development of a context-aware chatbot to serve farmer users.
• Structure domain-specific prompts, curate local training datasets, and evaluate LLM performance.
• Collaborate with developers to deploy AI-based services into the platform’s front-end experience.
3. Data Integration and Collaboration
• Identify and explore complementary datasets from national or open data sources.
• Contribute to the design of data pipelines for integrating user-submitted (crowdsourced) data.
• Work collaboratively with the development team and provide analytical support as needed.

CANDIDATES WILL BE ASSESSED AGAINST THE FOLLOWING

Minimum Requirements

• University degree in Statistics, Data Science, Applied Mathematics, Computer Science, Agricultural Engineering, or a related field
• At least 3 years of relevant experience in data analysis and modelling using ML algorithms
• Working knowledge of English and Albanian
• National of Albania

FAO Core Competencies

• Results Focus
• Teamwork
• Communication
• Building Effective Relationships
• Knowledge Sharing and Continuous Improvement

Technical/Functional Skills

• Solid understanding of statistical modelling, multivariate, and classification techniques
• Coding proficiency in Python with libraries such as scikit-learn, pandas, numpy, tslearn, pytorch, mlflow, tensorflow, etc.
• Familiarity with version control (e.g., Github), reproducible workflows, and clear documentation
• Experience applying ML or DL models to real-world data problems
• (Asset) Experience with geospatial data processing libraries (e.g. rasterio, xarray, geopandas, json)
• (Asset) Familiarity with Google Earth Engine (GEE) for accessing and analyzing remote sensing data.
• (Asset) Experience with LLMs or chatbot frameworks (e.g., transformers, langchain, gradio, streamlit, etc)
• Experience working in agile development teams is an asset.
• Ability to collaborate with designers, back-end developers, and end-users.

Selection Criteria

• Proficiency in Python for data analysis and model development is essential
• Proven analytical thinking and ability to implement and interpret statistical and ML models
• Ability to write efficient, reusable, and well-documented code
• Strong communication skills and ability to collaborate in a multi-disciplinary, international team
• Familiarity with agriculture and rural development topics is a plus
• Willingness to learn and apply geospatial and EO tools with guidance from senior advisors
• Strong attention to detail, proactiveness and curiosity.
• Strong problem-solving and time-management skills.
• Ability to collaborate effectively with team members.
• Ability to work independently.

Please note that all candidates should adhere to FAO Values of Commitment to FAO, Respect for All and Integrity and Transparency.

ADDITIONAL INFORMATION

• FAO does not charge a fee at any stage of the recruitment process (application, interview meeting, processing).
• Incomplete applications will not be considered. If you need help or have queries, please contact\: Careers@fao.org
• Applications received after the closing date will not be accepted.
• Only language proficiency certificates from UN accredited external providers and/or FAO language official examinations (LPE, ILE, LRT) will be accepted as proof of the level of knowledge of languages indicated in the online applications.
• For other issues, visit the FAO employment website\: http\://www.fao.org/employment/home/en/
• Appointment will be subject to certification that the candidate is medically fit for appointment, accreditation, any residency or visa requirements, and security clearances.

HOW TO APPLY

• To apply, visit the recruitment website at Jobs at FAO and complete your online profile. We strongly recommend that your profile is accurate, complete and includes your employment records, academic qualifications, and language skills
• Candidates are requested to attach a letter of motivation to the online profile
• Once your profile is completed, please apply, and submit your application
• Candidates may be requested to provide performance assessments and authorization to conduct verification checks of past and present work, character, education, military and police records to ascertain any and all information which may be pertinent to the employment qualifications
• Incomplete applications will not be considered
• Personal information provided on your application may be shared within FAO and with other companies acting on FAO’s behalf to provide employment support services such as pre-screening of applications, assessment tests, background checks and other related services. You will be asked to provide your consent before submitting your application. You may withdraw consent at any time, by withdrawing your application, in such case FAO will no longer be able to consider your application
• Only applications received through the FAO recruitment portal will be considered
• Your application will be screened based on the information provided in your online profile
• We encourage applicants to submit the application well before the deadline date.

If you need help or have queries, please create a one-time registration with FAO’s client support team for further assistance\: https\://fao.service-now.com/csp

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