Jake Mathew

Background

About Jake Mathew

Jacob Mathew is a Data Scientist at Kyndryl, where he designs and deploys machine learning solutions that drive operational efficiency and innovation across enterprise systems. With a strong foundation in Python, R, and cloud technologies like Azure, Jacob has led and contributed to a range of impactful projects—from forecasting service requests to modernizing mainframe infrastructure. His recent work includes developing a Retrieval-Augmented Generation (RAG) system that interprets JCL and COBOL code using Azure OpenAI and Neo4j, enabling enhanced data lineage tracking for mainframe modernization. He also built a forecasting tool that predicts Request for Service (RFS) volumes with mean absolute percentage errors as low as 8%, helping teams optimize resource allocation. Jacob co-led the creation of an anomaly detection tool for the Pediatric Heart Transplant Society and developed NLP models that flag off-menu consult requests with 90% precision. Jacob’s contributions have been recognized through a Kyndryl Hackathon win, where he was one of nine winners among 290 teams. He previously interned at Kyndryl, where he helped rebuild IT infrastructure for a state mining department and prototyped NLP models for internal skills mapping. He holds an Honors Bachelor of Science in Mathematics from the University of Toronto, with minors in Statistics and Anthropology. Jacob is also a Microsoft Certified Azure Data Scientist Associate. He is passionate about learning new technologies and staying up to date on the latest academic research in his field