Charles Earl is a Principal Data Scientist with 14 years of experience building machine learning and cloud-native systems that power social recommendation and secure cloud computing. He has held senior roles at Crexi and GitHub and spent five years shaping data science at Automattic, bringing product-focused ML into production at scale. His background spans research and engineering—from Hadoop and large-scale analytics for enterprises to founding a cloud platform startup for scientific collaboration. Charles holds a PhD in Computer Science from the University of Chicago and pairs deep academic training with practical delivery across industry and research labs. He has a track record of turning research into deployed features such as automated news-video placement and churn prediction, and he gravitates toward problems that reshape how people work and exchange value. Based in Georgia, he blends systems-level thinking with product sensibility to move novel recommendation and security ideas into production.
14 years of coding experience
25 years of employment as a software developer
M.A. Education, M.A. Education at University of California, Berkeley
PhD Computer Science, PhD Computer Science at University of Chicago
B.S. Math, B.S. Math at Morehouse College
H.S., H.S. at Douglass High School
M.S. Electrical Engineering, M.S. Electrical Engineering at Georgia Institute of Technology
Contributions:85 commits, 16 PRs, 1 push in 4 years 7 months
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