Summary
Kevin Schoelz is a Senior ML Engineer with a decade of experience applying data science and machine learning in the financial services sector at Arvest Bank, where he progressed from Division Data Science Analyst to Enterprise Data Scientist and now leads ML engineering efforts. He combines rigorous scientific training—a PhD in Physics and early research on graphene—with practical engineering skills in Python, SQL, cloud (Google Cloud), and automation to turn large, messy datasets into repeatable production pipelines. Kevin’s academic background and years as a physics instructor give him a strong foundation in experimental design, uncertainty quantification, and clear technical communication. He has hands-on experience parsing and loading hundreds of gigabytes of XML into relational schemas and accelerating analysis through scripting and automation. Based in Fayetteville, Arkansas, he’s finishing an MIS degree to bridge technical depth with information systems strategy, positioning him to deliver ML solutions that are both scientifically robust and operationally scalable. Colleagues benefit from his rare mix of research-grade rigor and pragmatic product-focused delivery.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Science (BS), Physics, Bachelor of Science (BS), Physics at Truman State University
Master of Information Systems (MIS), Information Systems, Master of Information Systems (MIS), Information Systems at University of Arkansas