Overview
Provide specialized technical support for the development and operationalization of Artificial Intelligence (AI)–enabled analytics within the UNFPA Supply Chain Management Unit (SCMU). The role supports the Supply Chain Orchestration and Analytics (SCOA) Hub and the UNFPA Supply Chain Control Tower.
Key Responsibilities
- Support the design and development of AI-enabled analytical capabilities within the Control Tower platform, including conversational access to data, automated insights, and AI-assisted risk identification.
- Develop analytical support tools for procurement, shipping, and inventory management teams.
- Collaborate with stakeholders to translate operational supply chain questions into AI-enabled analytical workflows.
- Develop prototypes and pilot tools demonstrating how AI can enhance the use of Control Tower data.
- Work with SCOA and IT Solutions Office (ITSO) teams to ensure AI capabilities are properly integrated with existing SCMU data systems and analytical platforms.
- Support the design of data pipelines enabling AI interaction with Control Tower datasets.
- Ensure compatibility with datasets including procurement pipelines, shipment tracking information, inventory monitoring data, and country supply chain performance indicators.
- Support the development of AI as an analytical layer that complements existing dashboards and systems.
- Ensure alignment with UNFPA data governance, digital strategy, and IT security frameworks.
- Support the identification, prioritization, and development of AI use cases for supply chain operations, such as procurement monitoring, shipment tracking, inventory risk alerts, forecasting, and performance analysis.
- Design and develop AI-enabled analytical tools and working prototypes, including natural language query interfaces, AI-driven insight generation tools, predictive analytics models, and AI-assisted reporting tools.
- Support SCMU in building internal capacity to utilize AI-enabled analytics through guidance materials, training sessions, and documentation.
Required Experience
- A minimum of five (5) years of progressively responsible experience in artificial intelligence or machine learning applications, data analytics and data engineering, development of AI-enabled analytical tools, data architecture and cloud-based data environments, development of analytical models and data-driven applications or related areas is required.
- Experience applying AI within operational or supply chain environments is highly desirable.
- Experience working with international organizations or development sector supply chains is considered an asset.
- Knowledge of data governance, responsible AI, and information security principles is desirable.
- Experience required in designing and maintaining data pipelines and working within cloud-based data environments.
- Proven ability to integrate APIs and manage data across diverse platforms.
- Demonstrated experience handling and analyzing large-scale operational datasets.
Qualifications
An advanced degree (minimum Master’s degree or equivalent) in Data Science, Artificial Intelligence, Computer Science, Information Systems, Supply Chain Analytics, or related areas is required.
