MICS-EMIS Data Analyst Consultant

UN Atlas; Toscana; Remote; EUR 60,000 - 90,000; Full time

Job summary

UNICEF is seeking a remote consultant to bolster the MICS-EMIS initiative by integrating education administrative data with household survey data across various countries. You will acquire, clean, and standardize datasets to enable comprehensive analysis of enrolment, progression, and learning outcomes.

Responsibilities include linking datasets with MICS data, developing scalable reproducible processes, and ensuring data quality while adhering to UNICEF data protection policies.

Qualifications

• At least 4 years of experience in data analysis and building data pipelines.
• Experience with National Statistical Offices (NSO) and household survey data or large-scale datasets (e.g., MICS, DHS).
• Knowledge of data protection and UNICEF privacy policies.

Responsibilities

• Acquire, clean, and standardize education datasets from multiple countries for the MICS-EMIS initiative.
• Link cleaned education datasets with existing MICS household data to enable comprehensive analysis.
• Generate robust analytical insights on enrolment, progression and learning outcomes from the integrated data.
• Develop and document reproducible analytical processes, scripts, and tools scalable to other countries.
• Ensure data quality and integrity throughout data acquisition, cleaning and analysis.

Skills

Data analysis

Data pipelines

Household survey data

Job description

Work arrangement Remote / Home-based

Organizational Context

UNICEF operates in over 190 countries and territories, dedicated to saving children's lives, defending their rights, and helping them fulfill their potential from early childhood through adolescence. We are committed, passionate, and proud of our work, viewing the promotion of every child's rights not just as a job, but as a calling. UNICEF offers diverse opportunities for professional and personal development.

Job Purpose

This consultancy aims to bolster UNICEF’s MICS-EMIS initiative by integrating and analyzing education administrative data alongside household survey data. The goal is to achieve a more comprehensive understanding of enrolment, progression, and learning outcomes across various countries. The consultant will be responsible for acquiring, cleaning, and standardizing education datasets from multiple countries. A key aspect of the role involves linking these datasets with MICS data to generate insightful analytical findings. Furthermore, the consultant will develop reproducible processes and tools that can be effectively scaled and applied to additional countries, thereby enhancing UNICEF's data analysis capabilities and contributing to evidence-based decision-making for children's education.

Responsibilities

Acquire, clean, and standardize education administrative datasets from multiple countries for integration into the MICS-EMIS initiative. Link these cleaned education datasets with existing MICS household survey data to enable comprehensive analysis. Generate robust analytical insights on key education indicators such as enrolment, progression, and learning outcomes, drawing from the integrated datasets. Develop and document reproducible analytical processes, scripts, and tools that can be easily scaled and applied to other countries. Ensure data quality and integrity throughout the data acquisition, cleaning, and analysis phases. Collaborate with relevant UNICEF sections and country offices to understand data specificities and requirements. Prepare reports and visualizations summarizing analytical findings for various stakeholders. Contribute to the development of data management and analysis protocols for the MICS-EMIS initiative. Provide technical support and guidance on data analysis best practices. Ensure all data handling adheres to UNICEF's data protection and privacy policies. Document methodologies and code thoroughly to facilitate knowledge transfer and future use.

Work Experience

At least 4 years of experience in data analysis and building data pipelines. Experience working with National Statistical Offices (NSO) and household survey data or large-scale national/international assessment datasets (e.g., MICS, DHS) is required.

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