Consultancy, Supply Chain AI Specialist
Organizational Context
UNFPA is the lead UN agency for delivering a world where every pregnancy is intended, every childbirth is safe, and every young person's potential is fulfilled. The Supply Chain Management Unit (SCMU) is self-funded and tasked with ensuring effective and efficient delivery of life-saving reproductive health products. This consultancy supports the development and operationalization of AI-enabled analytics within the SCMU, specifically for the Supply Chain Orchestration and Analytics (SCOA) Hub and the UNFPA Supply Chain Control Tower.
Job Purpose
This consultancy aims to provide specialized technical support for developing and operationalizing Artificial Intelligence (AI)-enabled analytics within the UNFPA Supply Chain Management Unit (SCMU). The role will focus on enhancing the Supply Chain Orchestration and Analytics (SCOA) Hub and the UNFPA Supply Chain Control Tower. Under the guidance of the Supply Chain Orchestration and Analytics Specialist, the consultant will offer technical advisory and implementation support to build AI-driven analytical capabilities. This will improve decision-making, data usability, and the overall analytical value of the Control Tower data, contributing to more effective supply chain operations.
Responsibilities
The consultant will focus on applied AI solutions to strengthen supply chain decision support and enhance the Control Tower's data usability and analytical value. Key responsibilities include supporting the design and development of AI capabilities for the Control Tower, such as conversational data access, automated insights, and AI-assisted risk identification. The role involves integrating AI with the Control Tower's data architecture, working with SCOA and IT teams to ensure compatibility with various datasets and alignment with UNFPA's data governance and IT security frameworks. Additionally, the consultant will develop AI use cases for supply chain operations like procurement monitoring, shipment tracking, and inventory risk alerts, and create AI prototypes and analytical tools, including natural language query interfaces and predictive models. Knowledge transfer and capacity development for SCMU staff on AI-enabled analytics are also crucial.
Work Experience
A minimum of five years of progressive experience in AI/machine learning applications, data analytics, data engineering, and developing AI-enabled analytical tools is required. Experience applying AI in operational or supply chain environments is highly desirable. Experience in designing data pipelines, working with cloud environments, integrating APIs, and handling large-scale operational datasets is essential. Proficiency in analytical tools like Power BI or Python is also required.
Skills
Strong analytical and problem-solving capabilities are essential. The role requires the ability to translate operational needs into technical solutions, collaborate effectively across technical and operational teams, and communicate complex analytical solutions to non-technical stakeholders. Key behavioral competencies include integrity, commitment, embracing diversity and change, achieving results, accountability, and developing professional expertise.