• Support to the organization of the meetings of the Africa Regional Hub on big data, data science cafés, data science, and other data science-related meetings of ACS. • Support to the supervision of young data scientists in various data science projects and in the production of quality datasets for training machine learning algorithms. • Production of reports and presentations on big data, data science, and machine learning. • Development of a chatbot for finding statistical data and metadata on African countries.

• Assistance in the preparation and execution of data science hackathons and data science webinars.

• Contribution to various data science projects, code testing and supervision of other data scientists working on other data science projects. • Assistance to ACS in creating and maintaining a GitHub repository of code.

At its 45th session, the United Nations Statistical Commission voted to establish a UN Committee of Experts on Big Data and Data Science for Official Statistics (UN-CEBD) to examine further the benefits and challenges of Big Data, particularly the potential for monitoring and reporting on the SDGs.

In this context, the UN-CEBD and the wider official statistical community recognized the importance of adequately addressing issues such as methodology, quality, technology, data access, legislation, privacy, management, and finance, as well as providing adequate cost-benefit analyses for using Big Data.

To make this modernization endeavor more accessible and inclusive, four Regional Hubs for Big Data were established in 2020 and 2021 in Brazil (Rio de Janeiro), China (Hangzhou), Rwanda (Kigali), and the United Arab Emirates (Dubai).

These centers were mandated to encourage creative initiatives, exchange methodologies, algorithms, and tools, and teach the local community of official statisticians on Big Data and data science. The Regional Hubs will host international conferences and workshops on data science and the modernization of official statistics.

The National Institute of Statistics of Rwanda (NISR) and the United Nations Economic Commission for Africa collaborate to support the UN Global Platform Regional Hub for Africa. The collaboration was formalized by a Memorandum of Understanding (MOU) with the United Nations Department of Economic and Social Affairs (UNDESA).

The Regional Hub for Africa was established with the objective of: – Investigating the advantages and disadvantages of Big Data, – Monitoring and reporting on long-term development goals – Successfully enhancing official statistics with Big Data In addition, the 2022 session of the Statistical Commission for Africa stressed the importance of the modernization of statistical systems, and the recent Internet Government Forum that took place in Addis Ababa in 2022 also recognized that the statistical development momentum Africa has achieved in recent years must be sustained by enhanced data governance, transformational leadership, acquisition of new skills and knowledge including data science, Artificial Intelligence, and Machine Learning, to realize the new data ecosystems and unlock Africa’s full data potential.

As a result of the increase in demand for data, traditional National Statistical Systems are no longer able to cope, which is why National Statistical Systems need to be modernized and transformed.

It is now imperative to transform traditional data flows into broad data ecosystems that encompass the entire value chain of data, driven by national priorities and supported by the Fundamental Principles of Official Statistics outlined in the African Charter on Statistics, the Strategy for Harmonization of Statistics in Africa (SHaSA), and other existing policy frameworks.

In line with these modernization efforts, the data science programme of the African Centre for Statistics of the United Nations Economic Commission for Africa is exploring new and innovative ways to produce statistics using big data and data science and accompanying African national statistical systems in learning and applying such methodologies.

The African Centre for Statistics is planning to work in 2024 on the following workstreams in data science: – Use of alternative data sources (web scraping, satellite images, mobile phone data, etc.) to help in the production of various socio-economic indicators, including alternative well-being and beyond GDP indicators.

– Development of machine learning-powered systems to facilitate the exchange of knowledge and experiences between countries with a pilot project in the production of economic statistics (a chatbot combined with a system for matching queries with relevant records in a knowledge base).

In the long term, the systems will facilitate knowledge integration in areas where such integration is needed but still very challenging by tapping into the possibilities opened by the recent advances of data science research in language understanding and question answering.

– Generating datasets and training machine learning algorithms to classify economic regimes (different economic models’ outcomes) to improve inference in the production of economic statistics. – Any other relevant work in the areas of the governance and / or use of data science and machine learning to improve the production of official statistics that may arise as a priority work from the discussions with member countries.

Scope of work Under the overall supervision of the Director of the African Centre for Statistics and the direct supervision of the statistician in charge of data science-related workstream, the consultant is expected to perform the following tasks: – Support the organization of the regular meetings of the Africa Regional Hub on Big Data, Data science cafés and Data Science, and the other data science-related meetings of ACS.

– Help in the supervision of young data scientists in various data science projects and in the production of quality datasets for training machine learning algorithms.

– Help in the production of reports and presentations on big data, data science, and machine learning. – Help in the development of data analytics pipelines to support the data needs of ECA’s various publications. – Assist in the preparation and execution of data science hackathons and data science webinars.

– Contribute to various data science projects, code testing, and supervision of other data scientists working on other data science projects. – Assist ACS in the work of teh RPTC project on Big Data and Data Science.

– Assist ACS in creating and maintaining a GitHub repository of code. – Assist in any other data science-related activity as requested.

Advanced university degree (Master’s degree or equivalent) in a field related to ICT (Computer science, Data Science, Statistics, Information systems, or a related field) is required..A first-level university degree, in combination with qualifying experience, may be accepted in lieu of the advanced university degree.

A minimum of 3 years of practical experience in data science is required.

Knowledge of developing countries and issues related to statistical development, SDGs and Agenda 2063 is required. Good communication, presentation, and writing skills are desirable. Good understanding and use of the following tools is desirable: R, Python, MySQL, HTML, CSS, SQL, JQuery, JavaScript, JSON, Web services/APIs; GitHub, Visual Studio Code. Experience in supporting data science projects in the context of the UN is desirable.

THE UNITED NATIONS DOES NOT CHARGE A FEE AT ANY STAGE OF THE RECRUITMENT PROCESS (APPLICATION, INTERVIEW MEETING, PROCESSING, OR TRAINING).

THE UNITED NATIONS DOES NOT CONCERN ITSELF WITH INFORMATION ON APPLICANTS’ BANK ACCOUNTS.