Azam Khan is a skilled Business Analyst at Thomson Reuters since October 2024, specializing in the analysis and reporting of large language models (LLMs) to enhance organizational performance and partnerships. Previously, Azam served as a Learning Support Practitioner at Colchester Institute, where initiatives led to increased student engagement and academic performance. Additionally, as a Data Analyst at Evamp & Saanga, predictive models developed improved project success rates and customer satisfaction in telecom and fintech solutions. Azam's foundational experience includes a role as a Supply Chain Associate at FF STEEL, where hands-on exposure to various operational functions fostered efficiency improvements. Azam holds a Master's degree in Data Science from the University of Essex and a Bachelor's degree in Mechanical Engineering from the University of Engineering & Technology Peshawar.