Mike Hyde
About Mike Hyde
Mike Hyde serves as the Chief Data Officer at Trainline, where he has worked since 2021. Previously, he held key data science roles at Facebook and Skype, and he possesses extensive expertise in user behavior analytics and data strategy.
Work at Trainline
Mike Hyde serves as the Chief Data Officer at Trainline, a role he has held since 2021. In this position, he focuses on creating data strategies and fostering a data-driven culture within the organization. His leadership involves overseeing data planning and implementation to enhance decision-making processes across the company.
Previous Experience at Facebook
Before joining Trainline, Mike Hyde worked at Facebook as the Director of Data Science from 2017 to 2021. During his tenure in London, he managed large-scale data initiatives and contributed to the development of analytics strategies that informed user engagement and product development.
Career Background
Mike Hyde has a diverse career in data science and analytics. He previously held positions at Microsoft as the Director of Business Insights for Skype from 2013 to 2016, and at Opera Solutions as a Senior Engagement Manager from 2005 to 2010. His experience includes managing significant consumer data sets and applying data analytics to solve business challenges.
Education and Expertise
Mike Hyde studied at the University of Cambridge, where he earned a Master of Engineering (M. Eng.) in Information Sciences from 1996 to 1997 and a Master of Arts (M.A.) in Engineering, Physics, and Computing from 1993 to 1996. His expertise encompasses user behavior analytics, profitability modeling, and performance analysis, along with experience in global offshoring and commercial negotiation.
Achievements in Data Science
Throughout his career, Mike Hyde has been involved in building cross-functional data teams and implementing large-scale experimentation to address business problems. He has worked with global clients across various sectors, including Financial Services, Media, Telecommunications, and Manufacturing, applying data analytics to enhance customer value and marketing strategies.