Result of ServiceThe consultant will deliver an updated guiding document on the analysis of household surveys with R, emphasizing data disaggregation and the production of reliable estimates using Small Area Estimation (SAE) models. In addition, the consultant will produce a complete set of revised training materials for the 2025 course, including lecture notes, case studies, coding exercises, and practice datasets, all adapted to the Latin American context and aligned with the latest methodological standards. Work LocationWorking remotely Expected duration20.09.25-20.10.25 Duties and ResponsibilitiesThe ECLAC Statistics Division, in collaboration with the United Nations Statistics Division (UNSD), offers an annual virtual course on Data Disaggregation using Small Area Estimation (SAE) Models for staff from National Statistical Offices (NSOs) in Latin America. This training initiative seeks to strengthen the technical capacities of NSOs to produce reliable indicators that support the 2030 Agenda for Sustainable Development, particularly in monitoring progress toward the “leaving no one behind” mandate. The course combines theoretical modules with practical exercises using household survey microdata, focusing on the application of Small Area Estimation (SAE) techniques with the statistical software R. Since its first edition, it has become an important reference for methodological training in the region. However, to maintain its relevance and effectiveness, it is necessary to update the technical materials, case studies, and learning resources in line with recent methodological advances, updated data sources, and the latest versions of R packages. For the 2025 edition, the Division requires the support of a consultant to revise, update, and improve the academic and technical materials used in the course, ensuring their applicability to current challenges faced by NSOs. This work will be conducted under the supervision of the Regional Advisor on Social Statistics. The consultant will be responsible for the following activities: - Revision and update of the guiding document on the analysis of household surveys with R, with emphasis on data disaggregation and the production of reliable estimates using SAE models. - Development and enhancement of training materials, including lecture notes, case studies, coding exercises, and datasets, ensuring that examples are relevant to the Latin American context and aligned with the latest methodological standards. Qualifications/special skillsUniversity degree and PhD in Statistics or a related field are required. Minimum of five years of professional experience in the design and analysis of household surveys is required. Demonstrated experience in the design and analysis of household surveys is required. Proficiency in R for statistical computing is required. LanguagesAdvanced knowledge of Spanish is required. Additional InformationNot available. No FeeTHE 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.