Philip Goddard
About Philip Goddard
Philip Goddard serves as the Head of Data Science, Quant, and Machine Learning Engineering at Kindred Group plc, where he leads a team of 40 professionals. He holds a Ph.D. in Theoretical Physics from the University of Surrey and has extensive experience in data science across various organizations.
Work at Kindred Group
Philip Goddard currently serves as the Head of Data Science, Quant, and Machine Learning Engineering at Kindred Group plc. He has held this position since 2021, leading a team of 40 professionals in the fields of data science, quantitative analysis, and machine learning engineering. His role involves developing solutions for various business areas, including pricing, personalization, risk management, retention marketing, and cybersecurity. Philip has also transformed the data science team at Kindred Group from a project-based approach to a product-led organization, enhancing the team's operational efficiency and output.
Education and Expertise
Philip Goddard studied at the University of Surrey, where he earned a Master of Physics (MPhys) degree from 2007 to 2011. He furthered his education at the same institution, achieving a Doctor of Philosophy (Ph.D.) in Theoretical Physics from 2011 to 2014. His academic background provides a strong foundation for his expertise in data science and machine learning, which he applies in his current role at Kindred Group.
Background
Before joining Kindred Group, Philip Goddard gained experience in various data science roles. He worked at HACT Housing as a Data Scientist from 2015 to 2016 and then at Sainsbury's in the same capacity from 2016 to 2017. He returned to Kindred Group in 2019, initially as a Senior Data Scientist II, before progressing to Lead Data Scientist and ultimately to his current position. His diverse experience across different organizations has contributed to his comprehensive understanding of data science applications in various industries.
Achievements
At Kindred Group, Philip Goddard has been instrumental in building the organization's capability to deliver an algorithmic data strategy for its proprietary Sportsbook platform. He supports retention marketing and player sustainability initiatives through data science efforts, ensuring that the organization leverages data effectively to enhance user experience and operational performance.