Consultancy, Supply Chain AI Specialist

The consultancy provides specialized technical support for developing and operationalizing AI-enabled analytics within the UNFPA Supply Chain Management Unit, supporting the Supply Chain Orchestration and Analytics Hub and the Supply Chain Control Tower. The role involves technical advisory and implementation support for AI analytical capabilities to enhance supply chain decision support and data usability.

Responsibilities

• Support the design and development of AI-enabled analytical capabilities within the Control Tower platform, including conversational access to supply chain data through natural language queries, automated analytical insights, AI-assisted identification of supply chain risks, and development of analytical support tools for procurement, shipping, and inventory management teams.
• Collaborate with SCMU 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 teams to ensure AI capabilities are properly integrated with existing SCMU data systems and analytical platforms, including supporting the design of data pipelines and ensuring compatibility with various datasets.
• Support the development of AI as an analytical layer complementing existing dashboards and systems, ensuring alignment with UNFPA data governance, digital strategy, and IT security frameworks.
• Support the team in development of AI use cases that directly support supply chain operations such as procurement pipeline monitoring, shipment tracking and delay detection, inventory risk alerts and stock-out prediction, forecasting and supply planning support, and country supply chain performance analysis.
• Design and develop AI-enabled analytical tools and working prototypes demonstrating practical value for SCMU operations, 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 development of guidance materials, training sessions, documentation of AI models and tools, and contribution to building internal data literacy and AI readiness.

Requirements

• 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.
• 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.
• Proficiency in analytical tools such as Power BI, Python, or similar environments is essential.
• Demonstrated experience handling and analyzing large-scale operational datasets.
• Fluency in English is required.
• Working knowledge of any other UN official language is an asset.

Skills

• Artificial Intelligence
• Machine Learning
• Data Analytics
• Data Engineering
• AI-enabled Analytical Tools
• Data Architecture
• Cloud-based environments
• Analytical Model Development
• Data-driven Applications
• Supply Chain AI Applications
• Data Governance
• Responsible AI Principles
• Information Security Principles
• Data pipeline design
• API Integration
• Power BI
• Python
• Large-scale Dataset Analysis

Languages

English