Scott Knox
About Scott Knox
Scott Knox is a Machine Learning Engineer with extensive experience in applying machine learning techniques to business problems. He has worked at various organizations, including Measurabl, 12traits, Northrop Grumman Corporation, and currently at MINDBODY, where he focuses on enhancing customer experience through machine learning models.
Work at MINDBODY
Scott Knox has been employed at MINDBODY as a Machine Learning Engineer since 2020. In this role, he focuses on developing machine learning models that enhance customer experience. His work involves applying both traditional and advanced machine learning techniques to address complex business challenges. Knox's contributions aim to improve the overall service and functionality offered by MINDBODY, which is known for its wellness and business management solutions.
Previous Experience in Data Science
Before joining MINDBODY, Scott Knox worked at 12traits as a Data Scientist from 2019 to 2020. His experience also includes a three-year tenure at Measurabl, where he served as a Data Scientist from 2016 to 2019. In these positions, he applied his expertise in data analysis and machine learning to solve various business problems. Additionally, he worked at Northrop Grumman Corporation as a System Engineer in Modeling and Simulation from 2013 to 2016.
Education and Expertise
Scott Knox holds a Bachelor of Science degree in Mathematics from UC Santa Barbara, where he studied from 2005 to 2009. He also earned a Master of Science in Applied Mathematics with a focus on the Theory of Communication Systems from San Diego State University, completing his studies from 2011 to 2013. Furthermore, he obtained a Master of Advanced Study in Data Science and Engineering from UC San Diego, studying from 2014 to 2016. His educational background supports his expertise in applying machine learning techniques to business challenges.
Research Assistant Role
Scott Knox served as a Research Assistant at San Diego State University from 2012 to 2013. In this role, he contributed to various research projects, leveraging his knowledge in mathematics and data analysis. His experience as a research assistant provided him with practical skills that have been beneficial in his subsequent roles in data science and machine learning.