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 focuses on enhancing 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, AI-assisted risk identification, and development of analytical support tools.
- Collaborate with stakeholders to translate operational supply chain questions into AI-enabled analytical workflows and develop prototypes.
- Work with SCOA and IT Solutions Office (ITSO) teams to integrate AI capabilities with existing SCMU data systems and analytical platforms, supporting data pipeline design and ensuring compatibility with various datasets.
- Support the development of AI use cases for supply chain operations, such as procurement monitoring, shipment tracking, inventory risk alerts, and forecasting.
- 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 developing guidance materials, supporting training sessions, and documenting AI models and tools.
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.
- 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 university degree (Master’s degree or equivalent) in Data Science, Artificial Intelligence, Computer Science, Information Systems, Supply Chain Analytics, or a related field is required. A first-level university degree (Bachelor’s degree or equivalent), combined with additional years of relevant professional experience, may be accepted in lieu of the advanced degree.
