FLS Data Analyst

Develops a reproducible composite indicator of schooling and learning deprivation from MICS data across 44 countries, validates it against established education measures, and creates an interactive public-facing visualisation and documented annual update workflow for UNICEF.

Department: Data & Analytics Section, MICS, Office of Strategy and Evidence

• Review country-level conditions affecting implementation of the MICS Foundational Learning Skills module
• Write reproducible R code to calculate reading and numeracy indicators across 44 countries and territories
• Adjust indicator calculations for differences in assessment administration protocols
• Manage analytical outputs through a structured Git repository
• Validate the composite indicator against ECDI and SDG 4.1.1 measures
• Develop an interactive product with at least 15 data visualisations focused on equity and learning gaps
• Prepare reproducibility documentation and an operational annual update workflow
• Store and organise the update workflow on GitHub and SharePoint for institutional use

• Master’s degree in psychometrics for educational assessment or a similar field
• At least two years of experience analysing educational assessments, preferably reading and mathematics assessments
• Experience with large-scale assessment instruments
• Experience with household survey data or large-scale national or international assessment datasets
• Proficiency in psychometric analysis software
• English is required

• Remote ten-month individual consultancy
• Applicants must submit a TMS profile, CV, cover letter and separate financial proposal