Consultancy: Advanced Analysis of Learning Assessment Data (AMPL)

JOB DETAILS

Type of contract : Consultant Contract

Level : Level 3 - Senior

Hiring Unit : Institute for Statistics (UIS)

Duty Station : Montreal

Work location : Remote

Duration of contract : 6 months

Hiring open to : External candidates

Application deadline (Midnight UTC−4 Time) : 24/07/2026

UNESCO Core Values: Commitment to the Organization, Integrity, Respect for Diversity, Professionalism

OVERVIEW

As the custodian agency for SDG 4 indicators, the UNESCO Institute for Statistics (UIS) supports countries in generating and using data on student learning outcomes to inform education policy and monitor progress towards SDG indicator 4.1.1. The Assessment for Minimum Proficiency Levels (AMPL) is one of UIS's flagship modules to produce and report internationally comparable SDG 4.1.1 indicators. More than a dozen countries have completed main AMPL test administrations, and additional countries are implementing AMPL in different languages across all regions.

While AMPL provides structured and internationally comparable datasets, many countries face limitations in applying advanced analytical approaches to these datasets and to their broader national assessment data systems. As a result, existing data remain underutilized in identifying key determinants of learning outcomes, understanding disparities across population groups, sub-regions and schools, and informing targeted policy interventions.

UIS is therefore seeking a consultant (or consultant team) to: (a) generate policy-relevant analytical outputs on learning quality and equity using AMPL datasets, working together with country teams as co-authors; and (b) strengthen national capacity to independently apply advanced statistical methods to learning assessment data in selected countries. The consultancy is framed by two UIS studies by Douglas J. Willms: Learning Divides: Ten Policy Questions about the Performance and Equity of Schools and Schooling Systems (2006) and Learning Divides: Using Data to Inform Educational Policy (2018).

ASSIGNMENTS

Under the overall authority of the Head of the Foresight, Research and Methodological Innovation (FRM) Section, and in close collaboration with national assessment teams, the consultant will implement a six-month phased programme combining structured training, hands-on application and technical mentoring, centred on two in-person workshops. Specifically, the consultant will:

• Preparation (Weeks 1–6): Assess the availability and readiness of AMPL datasets; develop a common analytical framework addressing key policy questions on learning outcomes, equity and school/system-level effects; and prepare a training materials package covering advanced statistical methods (multilevel modelling and regression-based approaches), supported by practical tools such as annotated code and replicable templates adaptable to national assessment data.
• Workshop 1 (in-person; location TBC; tentatively Weeks 7–8): Introduce advanced analytical methods and apply them to country datasets, including hierarchical (multilevel) models suited to clustered education data; support country teams to define analytical questions, develop models and produce initial findings.

Long Description

• Inter-sessional support (Weeks 9–18): Provide remote technical support as country teams deepen their analyses, refine models and extend approaches to broader national learning assessment datasets where available; support the development of draft country analytical reports using standardized templates.
• Workshop 2 (in-person; location TBC; tentatively Weeks 19–20): Facilitate peer review of country analyses; support refinement of results with emphasis on policy interpretation and translating findings into actionable messages; guide discussions on institutionalizing analytical practices within national systems.
• Finalization (Weeks 21–24): Finalize country reports; consolidate technical tools and guidance into a practical toolkit; produce a synthesis report summarizing cross-country findings, lessons learned and recommendations; and support dissemination planning.

The target audience will be two to three technical staff per participating country, drawn from national assessment units or the relevant ministry responsible for learning assessments and SDG 4.1.1 reporting. The consultant will participate in monthly progress calls with the UIS team and submit all deliverables for review prior to finalization.

CONTRACT DURATION

The contract duration is 6 months, structured around the five phases in the work plan: Preparation (Weeks 1–6), Workshop 1 (Weeks 7–8), Inter-sessional support (Weeks 9–18), Workshop 2 (Weeks 19–20), and Finalization (Weeks 21–24).

DELIVERABLES

1. Analytical framework document and training materials package (including annotated code and templates) – end of Week 6.
2. Workshop 1 delivered; draft country analytical models and preliminary findings – end of Week 8.
3. Draft country analytical reports (one per participating country) – end of Week 18.
4. Workshop 2 delivered; revised country reports and policy briefs – end of Week 20.
5. Final country reports, cross-country synthesis report and practical toolkit (code, templates and methodological notes) – end of Week 24.

Payment will be linked to the satisfactory delivery and acceptance of the deliverables listed above, in accordance with UNESCO procedures.

Long Description

TRAVEL

The consultancy will require international travel to support the delivery of the two in-person workshops and, where relevant, engagement with participating countries. Travel arrangements will be agreed with UIS in advance and in accordance with UNESCO rules and procedures.

COMPETENCIES - Core (C) & Managerial (M)

• Communication (C)
• Accountability (C)
• Innovation (C)
• Knowlegde sharing and continuous improvement (C)
• Planning and organizing (C)
• Results focus (C)
• Teamwork (C)

For detailed information, please consult the UNESCO Competency Framework.

REQUIRED QUALIFICATIONS

EDUCATION

• A PhD or equivalent advanced degree in statistics, econometrics, psychometrics, or a related field; OR a Master's degree in a related field with a minimum of seven (7) years of relevant professional experience.

WORK EXPERIENCE

• Demonstrated expertise in analysing large-scale assessment data, including familiarity with AMPL, MILO, or equivalent international learning assessment programmes.
• Strong experience in multilevel modelling and complex survey data analysis.
• Proven experience in capacity building and training delivery, demonstrated by at least five (5) years of experience or three (3) comparable assignments, with references available upon request.

Long Description

SKILLS AND COMPETENCIES

• Proficiency in at least one statistical software package (e.g. R, Stata) for large-scale assessment data analysis.
• Ability to design and deliver effective training and mentoring for national technical teams.
• Excellent drafting skills, with proven ability to produce clear analytical reports, policy briefs and technical guidance for diverse audiences.
• Ability to work independently in a remote setting, manage concurrent country engagements and meet deadlines.

LANGUAGES

• Excellent proficiency in English (written and spoken) is required.
• Working knowledge of French is an asset.

APPLICATION PROCESS

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:

Part 1: Technical Proposal

• An up-to-date curriculum vitae;
• A statement of understanding of the assignment, indicating how the candidate's qualifications and experience make them suitable;
• The proposed methodology and detailed work plan for carrying out the assignment, including any inputs that may be required from UNESCO;
• Examples of similar work, with at least two (2) references from comparable assignments.

Part 2: Financial Proposal

• Daily rate and estimated level of effort, quoted in EUR/USD/CAD/GBP;
• Estimated travel costs and related expenses;
• Any other relevant cost elements.

Only complete applications received by the deadline will be considered. Responses to the mandatory pre-screening questions form an integral part of the application; candidates who do not meet the eliminatory criteria will not be considered further. Only shortlisted candidates will be contacted.

SELECTION AND RECRUITMENT PROCESS

Please note that all candidates must complete an on-line application and provide complete and accurate information, by the above deadline.

To apply, please visit the UNESCO Careers website. No modifications can be made to the application once submitted.

The process may include pre-recorded video interviews and/or written assessments, interviews with a Panel, as well as reference checks. In addition, candidates may be requested to provide additional information which may be pertinent to the position’s qualifications.

Please note that all candidates, whether selected or not, will be informed of the outcome of their application in due course.

Short-listed candidates may also be added to Talent Pools; subject to their consent (i.e. Data Privacy Statement).

ADDITIONAL INFORMATION

• UNESCO recalls that paramount consideration in the appointment of personnel 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.
• lndividuals 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.
• UNESCO does not charge a fee at any stage of the hiring process.