Michael Harper is a quantitative data scientist and consultant with 17 years of experience turning complex datasets into high-impact business and sports insights. He blends advanced statistical modeling, ML (Keras), and production data pipelines in Python, R, SQL and MongoDB to deliver multi-million dollar savings and product improvements across energy and sports domains. At ExxonMobil he led teams that produced patents and dozens of publications while saving $15M/year through automated pipelines; in sports he improved MLB draft and pitch-prediction models for the Milwaukee Brewers and built NBA and betting models for startups. Comfortable in Agile teams and cross-disciplinary leadership roles, he has mentored junior researchers, served on nonprofit boards, and earned awards for innovation and ethics. He pairs a PhD from MIT in chemical engineering with hands-on analytics expertise, and an unusual strength: translating first-principles experimental thinking into robust, production-ready predictive systems for both physical and behavioral data.
17 years of coding experience
15 years of employment as a software developer
Bachelor of Science - BS Chemical Engineering, Bachelor of Science - BS Chemical Engineering at University of California, Berkeley
Doctor of Philosophy - PhD Chemical Engineering, Doctor of Philosophy - PhD Chemical Engineering at Massachusetts Institute of Technology
The database of chemical parameters used with Reaction Mechanism Generator
Contributions:61 commits in 1 year 2 months
mechanismparametersreactionchemicaldatabase
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