Danielle Van Boxel is an Applied Math PhD candidate and data scientist in Tucson with 13 years of experience translating complex statistical problems into clear visualizations and production-ready insights. She builds specialized analytics and machine-learning workflows, creates practical video tutorials on neural networks, and acts as an effective technical liaison between contractors and customers. A fanatic about efficient computing workflows, she combines rigorous mathematical training with hands-on tooling to move projects from prototype to reproducible delivery. Known on GitHub as a self-styled "Data Witch" and hex editor enthusiast, she brings a curiosity-driven approach to debugging and instrumentation that often surfaces nonobvious improvements to pipelines.
Contributions:101 commits, 70 pushes, 3 branches in 8 years
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