Conrad Koziol is an applied scientist with a PhD from the University of Cambridge and a decade of experience bridging physical sciences and machine learning to solve real-world problems. He has led end-to-end data projects from field geophysics to cloud-scale data center optimization, specializing in numerical modelling, time series, and satellite imagery. Conrad has commercialized deep-learning workflows for mineral prospectivity and accelerated prototype-to-production pipelines that cut project timelines by weeks or months. Comfortable in startup and enterprise settings, he has founded data science ventures and contributed to multidisciplinary teams at Microsoft and domain-focused consultancies. His background in polar science gives him a rare ability to translate complex physical uncertainty into robust, production-ready models.
10 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Polar Studies, Doctor of Philosophy - PhD Polar Studies at University of Cambridge
Bachelor of Science - BSc Honours Geophysics, Bachelor of Science - BSc Honours Geophysics at The University of British Columbia
Contributions:21 pushes, 1 branch in 2 years 3 months
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