Thomas Goter
Chief Data Officer
Kawaihae, Hawaii, United States
Summary
👤
Senior🎓
Top SchoolThomas Goter is a Chief Data Officer with eight years of professional data experience and a deep engineering foundation from a prior 14-year tenure at the Naval Nuclear Laboratory. He builds and leads high-performing teams that turn deterministic models and AI methods into operational decision-quality products, currently driving Govini’s data strategy and delivery. Thomas combines rigorous technical pedigree in nuclear engineering with a MIDS Data Science degree from UC Berkeley, enabling him to bridge complex domain physics and modern machine learning. He is equally comfortable shaping organizational data capabilities and diving into model design, validation, and deployment. Based in Kawaihae, Hawaii, he brings a pragmatic, mission-focused mindset honed in government and national-lab environments to commercial analytics challenges.
8 years of coding experience
16 years of employment as a software developer
MIDS Data Science, MIDS Data Science at UC Berkeley School of InformationBachelor of Science Nuclear Engineering, Bachelor of Science Nuclear Engineering at Missouri University of Science and Technology
Github Skills (4)
machine-learning2
data-augmentation2
deep-learning2
pytorch2
Programming languages (2)
Github contributions (5)
tomgoter/nlp_finalproject
Sep 2019 - Dec 2019
Contributions:115 commits, 112 pushes, 1 branch in 2 months
Berkeley-Data/irrigation_detection
Oct 2020 - Nov 2020
Contributions:146 commits in 1 month
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