ACS/Data Specialist

Organizational Context

The United Nations Economic Commission for Africa (ECA), in partnership with the United Nations Statistics Division (UNSD), is implementing a project to strengthen Africa's statistical ecosystem. This role supports the ECA's capacity to transform data into actionable insights through a robust analytics and AI layer built on the UN Data Commons, enhancing data integration and usability across the continent.

Job Purpose

This role provides hands-on technical support across the data lifecycle, from pipeline to policy, for the "Advancing Data Integration, Innovation and Capacity in Africa" project. The purpose is to enhance the ECA's ability to generate timely, actionable insights for policymaking by developing a scalable, AI-enabled data integration platform tailored for the African context. The consultant will be instrumental in designing and implementing data engineering workflows, developing analytical hubs, and creating an AI-driven prototype to support data-driven policy briefs, ultimately strengthening the African statistical ecosystem.

Responsibilities

Design and implement core data engineering workflows, including the integration of 7-12 regional and national datasets into the UN Data Commons schema. Collect, structure, clean, and preprocess datasets from multiple sources, ensuring completeness, consistency, and accuracy according to data quality frameworks. Optimize database performance and maintain database objects. Co-design, develop, and test two interactive, web-based Thematic Analytical Hubs with advanced visualization and reporting features. Develop an AI-enabled prototype for generating data-driven policy briefs, including managing data engineering and machine learning operations. Utilize the Analytical Hubs for policy analysis and contribute to producing at least six data-driven policy briefs. Produce technical documentation and contribute to capacity development programs for specialists.

Work Experience

Extensive experience with the entire data lifecycle, including frontend/backend web development, data engineering, data analysis, and data visualization is required. Proven experience managing large datasets, pipelines, and solving complex data engineering problems is desirable. Experience with open-source tech stacks is very helpful.

Skills

Data engineering, Data analysis, Data visualization, Frontend web development, Backend web development, Python, SQL, JavaScript, HTML/CSS, TypeScript, Power BI, Tableau, AI, Machine Learning Operations, Database management, Technical documentation.

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