John Burton
About John Burton
John Burton is a Data Science Chapter Lead at Brambles, where he has worked since 2022. He has extensive experience in data science and analytics, having held various roles in organizations such as HM Revenue & Customs, AQA, and the Cambridge Centre for Alternative Finance.
Work at Brambles
John Burton serves as the Data Science Chapter Lead at Brambles, a role he has held since 2022. Based in Manchester, United Kingdom, he leads a team of 15 data scientists and machine learning engineers. Under his leadership, the team focuses on developing innovative, data-driven products. The initiatives undertaken by his team are projected to generate over $500 million in value over the next three years. Additionally, he has established working standards and methodologies for data science teams, which are being adopted across the organization.
Education and Expertise
John Burton completed his Master of Science (MSc) in Physics at the University of Leicester from 2005 to 2009. He further pursued his education at Queen's University Belfast, where he earned a Doctor of Philosophy (PhD) in Astronomy between 2009 and 2014. His academic background is complemented by extensive experience in data science and analytics, contributing to his expertise in leading data-driven projects.
Background
John Burton's career spans various roles in data science and analytics. He began his professional journey as an Astronomer at Queen's University Belfast from 2009 to 2014. He then transitioned to academia as a Postdoctoral Researcher at York University in Canada from 2013 to 2015. Following this, he worked at the Cambridge Centre for Alternative Finance and held multiple positions at HM Revenue & Customs, including Skills & Capability Lead and Product Manager.
Achievements
John Burton received a NASA group award, recognizing his contributions to a significant project or collaboration. His leadership at Brambles Digital has led to the development of products that are expected to create substantial economic value. He has also played a pivotal role in establishing data science methodologies that are now being implemented organization-wide.