John currently serves as Lead Data Scientist at PokerStars, the world's largest online poker platform, where he has been instrumental in advancing the role of data science and machine learning within the company. He has led the development of a comprehensive portfolio of production models in areas that have a substantial impact on the business, including fraud modelling, player skill modelling, demand forecasting, and pricing optimisation.
With a strong background in mathematics and statistics, John brings a deep understanding of machine learning theory to his work. He is well-versed in a wide range of algorithms and technologies, ranging from traditional techniques from statistics to the more modern machine learning innovations of recent years. Additionally, John is passionate about cloud computing and MLOps and is highly adept at leveraging these tools to improve the performance, scalability, and robustness of models.
John holds an undergraduate degree in Mathematics and Statistics from University College Dublin and a Masters in Data Science from King's College London. He is an active member of the data science community and regularly attends conferences and events on topics related to data science, machine learning, and AI. He is a thought leader on these subjects within PokerStars and its parent company Flutter Entertainment, and his work is widely recognised for its technical rigour, business impact, and innovation.