John Savage
About John Savage
John Savage is a Staff Machine Learning Scientist at Overstock, where he has worked since 2023. He has a strong background in chemistry and machine learning, with previous roles at Deutsche Bank, Nuritas, and Baxter Healthcare, and has earned accolades for his contributions to data science and machine learning.
Current Role at Overstock
John Savage currently holds the position of Staff Machine Learning Scientist at Overstock, where he has been employed since 2023. His role is based in County Sligo, Ireland, and operates in a hybrid work environment. In this capacity, he focuses on leveraging machine learning techniques to enhance product offerings and improve operational efficiencies.
Previous Experience at Deutsche Bank
Prior to his current role, John Savage worked as a Data Engineer at Deutsche Bank from 2016 to 2017. This position was located in Dublin, Ireland, and lasted for one year. His experience at Deutsche Bank contributed to his expertise in data management and analytics.
Educational Background
John Savage has an extensive educational background in chemistry and machine learning. He earned a Master's Degree in Physical Chemistry from the University of Chicago, where he studied from 2011. He also completed a PhD in Theoretical Chemistry at the same institution from 2010 to 2015. Earlier, he obtained a Bachelor of Science in Chemistry from the University of Galway from 2004 to 2008.
Achievements in Machine Learning and Data Science
Throughout his career, John Savage has received recognition for his contributions to machine learning and data science. He won the Most Insightful award at a Chicago Bike Share data challenge and earned a silver medal in a Kaggle competition. Additionally, he led the implementation of an adaptive bidding product that significantly impacted the company's financial performance.
Contributions to the Community and Mentorship
John Savage actively contributes to the machine learning community. He has presented at PyCon Ireland in both 2016 and 2023 and has participated as a guest on the MLOps.community podcast and the Pathfinder podcast. As a Staff Machine Learning Scientist, he enjoys mentoring junior colleagues, focusing on enhancing communication and collaboration across teams to execute large-scale projects.