Summary
Pat Kenny is a senior data scientist with 12 years of experience applying physics-grade data engineering and machine learning to healthcare and life sciences. Trained as a PhD experimental physicist on the CMS experiment at CERN, he has mined 100+ terabyte datasets, run jobs on the worldwide LHC grid, and used Bayesian methods to extract tiny signals—skills he now applies to clinical analytics and predictive models. At Cerner he built speech-to-text, NLP, and computer vision pipelines to characterize clinical encounters, and at WellSky he focuses on bringing analytics across the continuum of health. He has hands-on experience across Python, C++, Linux, and reproducible notebook workflows, plus domain experience in microbial genomics and precision-animal-health algorithms from a startup environment. Comfortable mentoring students and collaborating in fast-paced international teams, Pat combines rigorous experimental rigor with practical product-oriented delivery. An understated strength is his ability to translate high-energy physics tooling and large-scale data workflows into production-ready healthcare analytics.
12 years of coding experience
10 years of employment as a software developer
Bachelor of Science (BS), Physics, Bachelor of Science (BS), Physics at University of Kansas