Scaling up Data Science at Spotify

As a data scientist, working at a data-first company leads to many interesting opportunities and challenges. Providing relevant music recommendations is important, but even more essential is to have a holistic understanding of the user behavior. Spotify has one of Europe’s largest data clusters, and have recently started to migrate into the Google Cloud Platform. This allows us to scale up our analytical capabilities, but scaling up data science means more than just additional data storage and computational power. It also requires having an organization and culture with a data-first thinking in mind. Performing data science on petabyte-scale provide possibilities to find novel business insights, but also leads to new challenges. What do we use all the data for, what does it mean to be a data-first company, and how is data science being performed at Spotify? These are some of the questions that will be addressed in this talk.

Anders Arpteg

Anders Arpteg

Anders Arpteg has been working in both academia as an associate professor and in industry with machine learning and data science for 10+ years. He has previously been working with the Pricerunner founders developing the next generation of information extraction systems, with real-time automated online marketing techniques for clients such as Netflix, and is now heading up a new Analytics Research team in Stockholm at Spotify.