Zachary King
About Zachary King
Zachary King is a Senior Manager in Machine Learning Science at Procter & Gamble, specializing in privacy-preserving technologies and computational cryptography applications.
Career at Procter & Gamble
Zachary King is currently a Machine Learning Science Senior Manager at Procter & Gamble, a position he has held since 2021. Before this role, he served as a Machine Learning Science Manager from 2020 to 2021. His work at Procter & Gamble involves leading machine learning initiatives and ensuring the implementation of advanced data science methodologies.
Experience at Axcess Financial
Before joining Procter & Gamble, Zachary King worked as a Machine Learning Scientist specializing in credit risk at Axcess Financial. Between 2019 and 2020, he spent 10 months in Cincinnati, OH, applying machine learning to enhance credit risk modeling and predictive analytics.
Work at The Cincinnati Insurance Companies
From 2016 to 2019, Zachary King held the position of Senior Predictive Modeler at The Cincinnati Insurance Companies. During his 3-year tenure in Cincinnati, OH, he focused on developing predictive models aimed at improving risk assessment and insurance underwriting processes.
Research Scientist Role at KEK
Zachary King served as a Research Scientist in Particle Physics at KEK from 2014 to 2016. Based in Tsukuba, Japan, and Cincinnati, OH, he worked on advanced research in particle physics, contributing to significant scientific advancements in the field.
Educational Background
Zachary King holds a Master of Computer Science in Machine Learning from Columbia University in New York, completed in 1970. He also earned a Bachelor of Science in Physics and Mathematics from the University of Cincinnati, where he studied from 2011 to 2015. His academic background provides a strong foundation for his expertise in machine learning and data science.
Specializations and Expertise
Zachary King specializes in privacy-preserving technologies designed to enhance consumer trust. His expertise includes computational cryptography applications, zero-knowledge, and trustless multiparty compute platforms. He also focuses on developing encrypted machine learning and reinforcement learning platforms, ensuring cutting-edge solutions in data science and machine learning fields.