John Caskey is a Data Engineer and seasoned data scientist with 11 years of experience applying computational biology, machine learning, and statistical methods to complex genomics and clinical datasets. At UW–Madison he builds production-ready pipelines and databases, including variant-calling workflows and LabKey systems, and has led ML projects for sepsis prediction and NLP-driven COVID contact tracing. Comfortable across Python, C++, Swift and R, he pairs hands-on software development with deep domain expertise in NGS, RNASeq, and biostatistics to translate between wet-lab scientists and computational teams. He routinely manages 5–15 cross-disciplinary projects concurrently and has a track record of turning bespoke research tools (including mobile apps and automation scripts) into scalable, reproducible workflows. Notably, his background spans both academic rigor (PhD in Biomedical Sciences) and practical productization, enabling rapid, creative solutions under pressure that prioritize accuracy and operational efficiency.
11 years of coding experience
14 years of employment as a software developer
Doctor of Philosophy (PhD) Biomedical Sciences, Doctor of Philosophy (PhD) Biomedical Sciences at Tulane University
Bachelor of Science (B.S.) Biology, Bachelor of Science (B.S.) Biology at Florida Atlantic University
Bachelor of Arts (B.A.) European History, Bachelor of Arts (B.A.) European History at The University of the South
Contributions:4 PRs, 5 pushes, 6 branches in 3 years 3 months
bioinformaticsgenomicannotationparsing
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