Peter Means
About Peter Means
Peter Means is the Director of Data Science and Machine Learning at Expedia Group, with over 15 years of experience in data science, strategy, finance, and product development.
Director, Data Science and Machine Learning at Expedia Group
Peter Means currently serves as the Director of Data Science and Machine Learning at Expedia Group. He has been in this role since 2021. Based in Austin, Texas, he operates in a hybrid working model. He employs machine learning and AI systems to enhance product features, contributing to significant profit and sales increases for the organization.
Past Roles at Expedia Group
Before his current role, Peter Means held various positions at Expedia Group. From 2018 to 2021, he was the Senior Manager of Data Science Strategy. Prior to that, he was the Manager of Data Science Strategy from 2017 to 2018 in the Austin, Texas area. His work involved strategic planning and the implementation of data-driven projects to improve business outcomes.
Experience in Finance and Analytics
Peter Means has extensive experience in finance and analytics. He worked as a Senior Manager of Finance and Strategic Analytics at The New Teacher Project from 2011 to 2013 in Austin, Texas. Prior to that, he was a Senior Analyst in Finance and Sales Analytics at Apple from 2009 to 2011 in Cupertino, CA. His earlier roles include a five-year tenure as Senior Analyst in the Finance Rotational Development Program at National Semiconductor and an internship in finance at Sun Microsystems.
Educational Background in Finance and Economics
Peter Means studied Finance and Economics at Santa Clara University, where he earned a Bachelor of Science (BS) degree. His educational background has fortified his understanding and application of financial principles in various strategic and analytical roles.
Expertise in Data Science and Product Development
With over 15 years of experience, Peter Means has advanced expertise in data science, strategy, finance, and product development. He is notable for spearheading machine learning initiatives that have contributed to sales and profit increases of more than $1 billion. His work integrates analytical rigor and business acumen to align and accelerate the adoption of AI systems.