DATA SCIENTIST

Job Description - Data Scientist (2403618) CALL FOR EXPRESSIONS OF INTEREST - VACANCY ANNOUNCEMENT: 2403618 Data Scientist Job Posting Job Posting: 28/Nov/2024 Closure Date Closure Date: 12/Dec/2024, 10:59:00 PM Organizational Unit: ESS - Statistics 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 persons 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’s commitment to environmental sustainability is integral to our strategic objectives and operations. 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. Rapid technological development requires ESS to innovate in various 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. We are seeking consultants and PSA subscribers with expertise in one or preferably more of the following areas, focusing on cutting-edge data science techniques, particularly in Natural Language Processing (NLP), and Artificial Intelligence (AI) methods: • Agricultural Data Science and Predictive Analytics: Utilizing AI methods such as machine learning models, LLMs, and data fusion techniques to analyze agricultural statistics, predict production trends, optimize trade decisions, and assess resource utilization. • Food Security and Nutrition Analytics: Employing NLP and LLMs to extract and analyze information from unstructured data sources, using AI for early warning systems, trend analysis, and policy evaluation in food security and nutrition. • Advanced AI-Driven Data Processing and Visualization: Leveraging Python, R, and other tools for AI-based data processing, predictive modeling, and dynamic visualization, integrating AI technologies to improve data insights. • Automated Data Collection and Text Mining Techniques: Utilizing AI and machine learning for enhanced data processing, including NLP for text mining, legal and policy documents analysis, and improving data quality through automated methods. • Integration of AI in Statistical Projects: Developing statistical projects that merge conventional statistical methods with cutting-edge AI techniques to innovate data collection, processing, and analysis practices. Reporting Lines Consultants and PSA subscribers will work under the immediate supervision of the Senior Statistician/Methodology Innovation Team Leader, and the general oversight of the Chief Statistician, Director and Deputy Director of ESS. Technical Focus The incumbent will develop and utilize advanced data science methods and AI techniques, with a focus on NLP and LLMs, to extract insights from large volumes of unstructured data and analyze information in agriculture, food security, and nutrition. Responsibilities include data processing, text mining, predictive modeling, and creating innovative solutions for data integration, automation, and visualization to enhance 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 statistics and data science methods, including the integration of AI and NLP techniques for innovative analyses. • Design and implement advanced methods, data collection processes, and analytical frameworks, utilizing a robust set of tools including R, Python, SQL and No-SQL databases, and related technologies (e.g. machine learning, NLP, crowdsourcing, text mining). • Drive the analysis, validation, and dissemination of complex datasets, employing AI and machine learning to enhance data interpretation and decision-making. • Utilize technologies for text mining and/or LLMs to extract insights from vast, unstructured data sets of documents. • Engage in statistical capacity development, providing technical assistance and training that covers both foundational statistical skills and modern data science and AI techniques. CANDIDATES WILL BE ASSESSED AGAINST THE FOLLOWING • Advanced university degree in data science, statistics, economics, computer science, or a related field. • At least 1 year of relevant experience in the field of data science, machine learning, natural language processing, artificial intelligence. • Working knowledge (level C) of English. FAO Core Competencies • Demonstrated proficiency and extensive experience in performing the above-mentioned tasks and responsibilities in relevant statistical or data science fields. • Experience in data exploration, preprocessing, and transformation techniques for handling diverse data types, including structured and unstructured formats. • Strong foundation in deploying, fine-tuning, and customizing Large Language Models (LLM) for NLP tasks. • Proficient in Python and R for data manipulation, model development, and deployment. • Ability to draft quickly, clearly, and concisely and to communicate effectively in English. • Ability to work independently, with minimum supervision. 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. Please note that FAO will only consider academic credentials or degrees obtained from an educational institution recognized in the IAU/UNESCO list. 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. • Incomplete applications will not be considered. #J-18808-Ljbffr