AI Engineer Consultant, Office of Strat & Evidence (OSE), - Data & Analytics Section -MICS - UNICEF Office of Strategy and Evidence - Innocenti, Florence, Italy / Remote - Req: 594724

Organizational Context

UNICEF works in over 190 countries and territories to save children’s lives, defend their rights, and help them fulfill their potential. We are committed, passionate, and proud of what we do for as long as we are needed. Promoting the rights of every child is not just a job – it is a calling.

Job Purpose

The UNICEF Data & Analytics (D&A) Education team is developing a data portal to consolidate information from various regional and global learning assessments. This Minimum Viable Product (MVP) will focus on foundational learning at Grade 4 and below, covering outcomes in reading and numeracy from programmes like TIMSS, PIRLS, EGRA/EGMA, MICS FLS, LLECE, AMPL, and ICAN/ICAR. The primary challenge is the heterogeneity of data documentation and structure across these programmes. This consultancy aims to establish a reproducible and scalable method for transforming this diverse data into harmonized tables ingestible by UNICEF's International Data Warehouse (IDW). The consultant will build the underlying data model, extraction pipeline, and reference datasets essential for the MVP portal's functionality.

Responsibilities

Develop and implement a robust data transformation strategy to harmonize diverse learning assessment data into a standardized format suitable for ingestion into UNICEF's International Data Warehouse (IDW). Design and build the underlying data model for the data portal, ensuring scalability and maintainability. Create and optimize data extraction pipelines to efficiently process and integrate data from various sources, including international reports, technical annexes, almanac spreadsheets, and microdata. Develop reference datasets that will serve as the foundation for the MVP data portal. Ensure the reproducibility and scalability of all data transformation processes. Collaborate with the UNICEF Data & Analytics (D&A) Education team to define data requirements and validate the harmonized datasets. Document all data models, pipelines, and transformation methodologies thoroughly. Provide technical guidance and support to the team on AI and data engineering best practices. Contribute to the overall architecture and design of the data portal. Troubleshoot and resolve any data-related issues that arise during the development and implementation phases.

Work Experience

At least 5 years of experience working with data structures, analysis, and building data pipelines. Experience with household survey data or large-scale national/international assessment datasets (e.g., MICS, DHS) is required.

Skills

Azure DevOps, Docker, Github, R programming, Python programming, Data structures, Data analysis, Data pipeline development, Household survey data, Large-scale assessment datasets, Data modeling, ETL processes

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