Support in the Development of Early Warning System - UNDSS HQ

Organizational Context

The UN Department of Safety and Security (UNDSS) provides global leadership and operational support for the UN security management system, ensuring the safest conduct of mandated activities. The Insight and Accountability Unit (IAU) at UNDSS Headquarters is spearheading an initiative on Early Warning System Development, aligning with UN 2.0 principles and the UNDSS Digital Transformation Strategy. This role supports the development and internal piloting of this crucial research.

Job Purpose

This assignment supports the Insight and Accountability Unit (IAU) at UNDSS Headquarters in developing an Early Warning Analysis system. The volunteer will contribute to research on publicly available datasets, focusing on machine learning tools and techniques. Key contributions include assisting with dataset consolidation, performing exploratory data analysis, and supporting the design, training, and evaluation of predictive models. The role also involves developing data visualizations and dashboards to communicate key insights effectively, ultimately enhancing the project's knowledge base and documentation.

Responsibilities

The online volunteer will contribute to the development of an Early Warning Analysis system by conducting research on publicly available datasets based on provided concept notes. Responsibilities include assisting with dataset consolidation as needed, performing exploratory data analysis, and supporting the design, training, and evaluation of machine learning models. Additionally, the volunteer will develop data visualizations and dashboards to present key insights derived from the analysis. The final deliverable will comprise analytical outputs and a comprehensive written report, enriched with visualizations, to contribute to the project's knowledge base and documentation.

Work Experience

A good understanding of machine learning principles, data analysis techniques, and report preparation is required. Hands-on experience in dataset preparation, data preprocessing, or model development is desirable. Familiarity with Microsoft Power Platform tools (e.g., Power BI) and previous involvement in data-driven projects or research studies are beneficial.

Skills

Proficiency in English (written and verbal) is essential. Key competencies include a strong understanding of machine learning principles, data analysis techniques, and report preparation. Desirable skills encompass dataset preparation, data preprocessing, model development, and familiarity with data visualization tools like Power BI. Experience with data-driven projects and analytical initiatives is also valued.

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