Consultancy: Enhancing the UIS Methodology for Calculating Regional Aggregates

Consultant

Overview

Review and enhance UIS aggregation methodology for education data.

You have:

• Advanced degree statistics, mathematics, education, economics, or a related field.
• Proven knowledge of international education statistics, including data sources, indicator methodologies, estimation techniques, and limitations.
• Extensive experience in statistical modeling, data analysis, large education databases, estimation and imputation of national-level data, and aggregation at international level.
• Excellent verbal and written communication skills in English.
• Familiarity with the International Standard Classification of Education (ISCED) and its application.
• Ability to work effectively in a remote environment.

Contract

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**OVERVIEW** ------------ Parent Sector : UNESCO Institute for Statistics (UIS) Duty Station: Montreal Classification of duty station: \[\[filter12\]\] Standard Duration of Assignement : \[\[filter13\]\] Job Family: Education Type of contract : Non Staff Duration of contract : From 1 to 6 months Recruitment open to : External candidates Application Deadline (Midnight Paris Time) : 06/06/2025 UNESCO Core Values: Commitment to the Organization, Integrity, Respect for Diversity, Professionalism **OVERVIEW OF THE FUNCTIONS OF THE POST** ----------------------------------------- **Background** Every year in August, the UNESCO Institute for Statistics (UIS) produces regional aggregates for a variety of education indicators. These groupings (regional averages) may be based on geography, income levels, or other classifications requested by UIS partners, such as the Global Partnership for Education (GPE). These indicators feed into global monitoring databases and reports and are disseminated as part of the official international education statistics. The national data underpinning these aggregates are sourced from publicly available official statistics. The quality of these aggregates is strongly influenced by the completeness of country-level data. This is particularly important for weighted averages, where countries with larger populations have a higher impact on the final aggregate. Missing data from populous countries is frequent and this can significantly impact the results. Further challenges arise from using population-based indicators that rely on population data from sources different from those used for education data, leading to occasional inconsistencies (e.g., population denominators exceeding education-related numerators in cases where this should not occur). Moreover, as many education indicators are interrelated, calculating them in isolation may result in internal inconsistencies. The current process for producing aggregates is time-consuming, inflexible, and limits the ability to respond quickly to emerging issues or data corrections. To address these concerns, UIS has initiated a review of its aggregation methodology and seeks to enhance the quality, reliability, transparency, and efficiency of its procedures. UIS seeks to engage a Senior Expert Consultant to develop the module on Legal Framework and Institutional Setup regarding Education Administrative data. Long Description ---------------- **Deliverables** Deliverable 1 (duration: 1 month) • Comprehensive review of the current UIS aggregation methodology and its implementation within the new UIS education data architecture and coding system (aligning with specifications from UIS Multi-Year Dynamic Template data collection). • Identification of methodological weaknesses and development of a detailed set of recommendations, for programming using Python (or R) codes. • A proposed roadmap for an enhanced aggregation methodology using Python or R codes and its implementation, including: o Estimation methods to improve data coverage at the national level; o Estimation and imputation approaches for indicators (at national level) with partial or missing data; o Mechanisms to ensure consistency across interrelated indicators; o Incorporation of confidence intervals; o Consideration of external shocks (e.g., COVID-19, natural disasters, or socio-political crises). Deliverable 2 (duration: 1 month) • Development of a pilot framework, including scripts (preferably in Python) and quality rating methods, for calculating aggregates focused on a core set of indicators. • Sensitivity analysis and testing of thresholds for data coverage, quality rating of aggregates, and confidence intervals. • Production of associated metadata for each aggregate, including: o Number of observed, estimated, and imputed data points; o Confidence interval. • Proposal for scaling the approach across all indicators produced through the UIS education data collection. Deliverable 3 (duration: 1.5 months) • Full-scale implementation of the new aggregation methodology. • Complete integration with the new UIS education data processes and associated data repository systems. • Delivery of documentation and tools supporting the new methodology. **COMPETENCIES (Core / Managerial)** ------------------------------------ Accountability (C) Communication (C) Innovation (C) Knowledge sharing and continuous improvement (C) Planning and organizing (C) Results focus (C) Teamwork (C) Professionalism (C) **-** ----- For detailed information, please consult the [UNESCO Competency Framework](https://en.unesco.org/sites/default/files/competency_framework_e.pdf). **REQUIRED QUALIFICATIONS** --------------------------- ***Education*** - Advanced degree statistics, mathematics, education, economics, or a related field. ***Experience*** - Proven knowledge of international education statistics, including data sources, indicator methodologies, estimation techniques, and limitations; - Extensive experience in statistical modeling, data analysis, large education databases, estimation and imputation of national-level data, and aggregation at international level; ***Language*** - Excellent verbal and written communication skills in English. **DESIRABLE QUALIFICATIONS** ---------------------------- ***Experience*** - Familiarity with the International Standard Classification of Education (ISCED) and its application. ***Skills*** - Ability to work effectively in a remote environment. **APPLICATION PROCESS** ----------------------- Interested candidates should complete the on-line application, download and complete the Employment History form (Word file). **At the end of the Word file, insert extra pages with the following required information:** 1. A cover letter outlining the candidate’s interest, qualifications, availability, and proposed consultancy fee; 2. An updated CV 3. Two samples of relevant work in statistical modeling, estimation/imputation for missing data, and aggregation, particularly in the context of international data or education. Only the proposals that include all the four aforementioned elements will be considered. Failure to provide any of those will result in an incomplete application which will not be considered. UNESCO places significant importance on achieving the objectives outlined in the Terms of Reference. Consequently, the evaluation of proposals will prioritize the technical components. From the proposals that meet the criteria specified in the Terms of Reference, UNESCO will select the one that provides the best value for money for the Organization. **SELECTION AND RECRUITMENT PROCESS** ------------------------------------- Please note that all candidates must complete an on-line application and provide complete and accurate information. To apply, please visit the [UNESCO careers website.](https://careers.unesco.org/careersection/2/joblist.ftl) No modifications can be made to the application submitted. The evaluation of candidates is based on the criteria in the vacancy notice, and may include tests and/or assessments, as well as a competency-based interview. UNESCO uses communication technologies such as video or teleconference, e-mail correspondence, etc. for the assessment and evaluation of candidates. Please note that only selected candidates will be further contacted and candidates in the final selection step will be subject to reference checks based on the information provided. **Footer** ---------- UNESCO recalls that paramount consideration in the appointment of staff members shall be the necessity of securing the highest standards of efficiency, technical competence and integrity. UNESCO applies a zero-tolerance policy against all forms of harassment. UNESCO is committed to achieving and sustaining equitable and diverse geographical distribution, as well as gender parity among its staff members in all categories and at all grades. Furthermore, UNESCO is committed to achieving workforce diversity in terms of gender, nationality and culture. Candidates from non- and under-represented Member States ([last update here](https://www.unesco.org/en/geo-distribution)) are particularly welcome and strongly encouraged to apply. Individuals from minority groups and indigenous groups and persons with disabilities are equally encouraged to apply. All applications will be treated with the highest level of confidentiality. Worldwide mobility is required for staff members appointed to international posts. UNESCO does not charge a fee at any stage of the recruitment process. Please note that UNESCO is a non-smoking Organization.

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Added 1 year ago - Updated 11 months ago - Source: careers.unesco.org