Summary
Chris Cotter is a Senior Data Scientist with 11 years of experience building production-grade ML systems that bridge research and business impact, currently leading predictive model R&D and productionalization. He has driven end-to-end solutions across GenAI, variational generative models, weak-label gene-target nomination, and spatiotemporal plant-trait pipelines that process >400k measurements annually, cutting turnaround from two weeks to 24 hours and reducing staffing needs from six FTEs to under one. A former academic who published in PNAS, he combines deep expertise in mutual-information–centric training, CNN segmentation, linear mixed models, and scalable MLOps on AWS/GCP with hands-on software engineering (Python, Docker, CI/CD, SQL). Notably, his patented and patent-pending work enabled gene-target discovery and automated production pipelines that moved models from notebooks into business-critical services. Based in Missouri, he focuses on turning vague ideas and messy real-world data into robust, measurable decisions for cross-functional stakeholders.
11 years of coding experience
12 years of employment as a software developer
Bachelor of Science (BS), Bioinformatics, Bachelor of Science (BS), Bioinformatics at Rochester Institute of Technology
Doctor of Philosophy - PhD, Microbiology (Focus on Applied Computational Methods), Doctor of Philosophy - PhD, Microbiology (Focus on Applied Computational Methods) at Unviersity of Georgia