Data Scientist

Job Description - Data Scientist (2400725)

Job Description

CALL FOR EXPRESSIONS OF INTEREST - VACANCY ANNOUNCEMENT : 2400725

Data Scientist

Job Posting

Job Posting

: 01/Mar/2024

Closure Date

Closure Date

: 15/Mar/2024, 10:59:00 PM

Organizational Unit : ESS

Job Type

Job Type

: Non-staff opportunities

Type of Requisition : Consultant / PSA (Personal Services Agreement)

Primary Location

Primary Location

: Italy-Rome

Duration : Up to 11 months on WAE basis with a possibility of renewal

Post Number : N/A

IMPORTANT NOTICE: Please note that Closure Date and Time displayed above are based on date and time settings of your personal device

• 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

Organizational Setting

The Statistics Division (ESS) develops and advocates for the implementation of methodologies and standards for data collection, validation, processing and analysis of food and agriculture statistics. In these statistical domains, it also plays a vital role in the compilation, processing and dissemination of internationally comparable data, and provides essential capacity building support to member countries. In addition, the Division disseminates many publications, working papers and statistical yearbooks, which cover agricultural and food security relevant statistics (including prices, production, trade and agri-environmental statistical data). The Statistics Division is involved in the management of a number of large-scale projects (50x2030, Global Strategy, FIES) aimed at improving statistical methodologies and establish best practices for the collection, collation, processing, dissemination and use of data relevant to food security, agriculture and rural areas.

Rapid technological development requires ESS to innovate in a variety of areas to modernize the statistical business process and meet the increasingly demanding needs for timely, accurate, and cost-effective data and analysis. Therefore, it is part of FAO’s strategy to engage with non-official, non-conventional, Big Data sources and to rely on data science and Artificial Intelligence methods to solve the current information gaps problems. The final objective is to expand the quantity, quality and range of the statistical and analytical products of the division. In this context, a Data Lab for Statistical Innovation has been established to lead the Division’s work related to modern data science applications with the objective to solve research problems in agriculture statistics and policy (e.g. policy analysis, use of statistics in policy making) by leveraging existing information.

Reporting Lines

Consultants and PSA subscribers will work under the immediate supervision of the Methodological Innovation Team Leader, or eventually another ESS Team Leader, and the general oversight of Director and Deputy Director of ESS. They may be called upon to collaborate with other FAO Divisions and teams.

Technical Focus 

We are seeking consultants and PSA subscribers with expertise in one or preferably more of the following areas, with focus on cutting-edge data science techniques, Natural Language Processing (NLP), Artificial Intelligence (AI), ideally including Large Language Models and/or Geospatial-AI:

• Sustainable Development Goals monitoring and indicators through advanced document analysis, information extraction, and big data analytics.
• Agricultural statistics, including production, trade, and utilization, enriched with predictive models and analyses.
• Food security, nutrition statistics, and other agricultural domains, leveraging advanced text analysis methods and large language models to extract actionable insights from unstructured data sources.
• Climate change, socio-economic, and environmental statistics, disasters loss and damage assessment, applying machine learning models, spatial models, and AI methods to address complex challenges in these fields.
• Advanced application of statistical/technical software languages like R and Python for programming, implementation and optimization of algorithms, data processing, analysis, and visualization.
• Technologies and methods for data collection, processing, and text mining, including the use of AI and machine learning for enhancing data management, quality and insights.
• Development and implementation of statistical projects that integrate conventional statistical methods with cutting-edge data science technologies and non-conventional sources (social media, web scraped and/or crowdsourced data, cellphone records, nightlights).

• GIS and satellite imagery application to obtain land use classification, feature extraction, object detection, and instance segmentation, preferably by applying AI methodologies to these tasks.
• Development of geospatial methods with the aim of obtaining Gross Domestic Product, sectoral value added, other socio-economic variables and other type of detailed geographical insights (e.g., displacement, aid development) at sub-national (very granular) and/or high frequency level, for contributing to a comprehensive understanding of regional dynamics for informed decision-making.

Tasks and responsibilities

In one or more of the above-mentioned statistical domains, Consultants and PSA subscribers will contribute to and/or take responsibility for one or more of the following tasks:
• Contribute to methodological development in data science methods, including the integration of AI and NLP techniques for innovative analyses.
• Design and implement data collection processes from non-conventional sources utilizing a robust set of tools including R, Python, SQL and No-SQL databases, and related technologies and paradigms (e.g., remote sensing, crowdsourcing, text mining, web scraping).
• Drive the analysis, validation, and dissemination of complex datasets, with data engineering methods and Artificial Intelligence to enhance data interpretation and decision-making.
• Utilize advanced algorithms and natural language processing techniques for text mining and/or Large Language Models to extract information from vast and unstructured data sets of documents to uncover hidden knowledge, enhance information retrieval, and contribute to a deeper understanding of complex narratives contained within extensive textual corpora.
• Develop and implement geospatial models to assess the impact of various factors on agricultural productivity, land use, and other relevant indicators, incorporating satellite imagery, GIS (Geographic Information System), and remote sensing technologies.
• Lead or assist in the creation, development, oversight, and innovation of statistical projects, aligning them with the latest advances in data science and technology.
• Engage in statistical capacity development, providing technical assistance and training that covers modern data science / Artificial Intelligence techniques.
• Support implementation of statistical policies that embrace innovative approaches to data analysis, with an emphasis on big data and non-conventional data sources, ensuring quality and relevance in the evolving landscape of agricultural and rural statistics.

CANDIDATES WILL BE ASSESSED AGAINST THE FOLLOWING

• University degree in statistics, economics, social sciences, computer science, data science, or a related and relevant field.
• At least one year of relevant experience in the above-mentioned areas of work and/or fields of application.
• For Consultants: Working knowledge of English, French or Spanish and limited knowledge of one of the other two or Arabic, Chinese, Russian. For PSAs: Working knowledge of one of the FAO languages.

FAO Core Competencies

Technical/Functional Skills
 
• Work experience in more than one location or area of work 
• Extent and relevance of experience in performing the above-mentioned tasks and responsibilities in relevant data science and/or Artificial Intelligence fields.
• Capacity to stay current with technical advancements in data science and AI, including a proactive approach to embracing future innovations in these fields.
• Strong command of data science and AI techniques including: natural language processing (NLP) and AI methods for text data analysis and language modeling; exploration, preprocessing and visualization of big data; handling complex structured and unstructured data; familiarity with a range of machine learning models such as decision trees, support vector machines; familiarity with advanced deep learning architectures such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs); expertise in transfer learning and reinforcement learning techniques; expertise in applying probability distributions and statistical principles within the context of predictive modeling and machine learning; proficiency in data manipulation and analysis with programming languages like Python or R, and tools such as Pandas, scikit-learn, NumPy, PyTorch, Keras, or TensorFlow; experienced in applying advanced dimensionality reduction techniques such as t-SNE and UMAP for feature extraction and visualization; knowledge in designing and implementing complex data collection strategies, including web scraping, API calls, and utilizing big data platforms like Hadoop or Spark for distributed data processing; expertise in model evaluation metrics and methods, including cross-validation, A/B testing, ROC curves, and confusion matrices; use of geospatial methods, applying GIS tools and methodologies for spatial analysis.
• Extent of practical knowledge of deploying and managing projects on major cloud platforms like Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure. This includes understanding how to leverage these platforms, and containerization and orchestration tools like Docker and Kubernetes, for scalable data processing, machine learning model training, and deployment.
• Extent of experience with the Git version control systems for collaborative development and code management.
• Ability to draft quickly, clearly and concisely and to communicate effectively in English.
• Ability to work independently, with minimum supervision.
• Previous working experience with FAO and its partners in the above-mentioned statistical domains and tasks would be an asset.
• Experience in the provision of technical assistance to countries and/or professional experience in national statistical services would be an asset.

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 any fee at any stage of the recruitment process (application, interview, processing)
• Please note that FAO will only consider academic credentials or degrees obtained from an educational institution recognized in the IAU/UNESCO list
• Please note that FAO only considers higher educational qualifications obtained from an institution accredited/recognized in the World Higher Education Database (WHED), a list updated by the International Association of Universities (IAU) / United Nations Educational, Scientific and Cultural Organization (UNESCO). The list can be accessed at
• 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: