Building a Recommendation Engine for a Sports Streaming Platform


DAZN is the world’s only globally operating Sports Video streaming company. It has over 150 different rights to Sports and competitions spread like a patchwork quilt over 200 countries. Organising the available content so that our customers can find what they want to watch can be challenging. In this talk you will see how product and engineering came together to understand the problem and build an in-house  solution for recommendations.


Hakki Deviren: Senior Product Manager Personalisation

Bio: Hakki cut his teeth on Tesco Clubcard before moving into DAZN where he quickly attained full responsibility for personalisation on the platform. He has overseen may successful initiatives including the Follow system which allows users to follow teams and competitions receive reminders on mobile and the recommendation system which will be presented today.

Thomas Northey: Head of Applied Machine Learning

Bio: Thomas started using ML techniques during his PhD before making the move away from academia. As the head of Applied Machine Learning, Thomas is responsible for implementing business-impacting ML methods from PoC to production. His team works on projects that span across the whole company, from content recommendation systems to demand forecasting.