Global IQ, a data-as-a-service company, supports multinational corporations in workforce planning through proprietary datasets and analytics tools. This project addresses the complex challenge of global talent mobility decisions like whether to deploy an expatriate, use short-term assignments, or hire locally, by building an LLM-based decision support interface. We deliver a system that optimizes global mobility decisions by integrating MCP capabilities with LLM-driven intelligence, enabling HR teams to receive clear, real-time, data-backed recommendations.
Watch the team present this project at 01:35:21 in the session recording here.
Keywords: Global mobility, talent optimization, large language models (LLMs), compensation modeling, policy optimization, MCP, HR Tech
Faculty Advisor
Gizem Agar, PhD is an expert in data analytics, machine learning, and transformation with a passion for mentoring. With 15+ years of interdisciplinary academic and industry experience, her latest work is in manufacturing, pricing, logistics, and supply chain. She has received the CEO Award and Outstanding Achievement in Analytics awards for her contributions to Caterpillar.
Dr. Agar teaches Principles of Data Mining, Python for Analytics, Supply Chain Optimization, Capstone courses and advises students. She holds a PhD and MSc in Industrial Engineering from University of Oklahoma, and BSc in IE and a BSc in CE from Cankaya University, Turkiye. She was a visiting scholar at the Kuhne Logistics University (Hamburg, Germany) and at the Technical University of Vienna (Vienna, Austria).