Questions? Read our FAQs
Questions? Read our FAQs
Any Spotify user can agree: Your Discover Weekly playlist is gold. But, despite how personalized it feels, it’s not your best friend pouring hours into this hyper-curated mixtape. It’s data science — algorithmically connecting the infinite data points between songs you like (and dislike), artists your friends like, and so on to forecast what you will like. With every skip, save, and share, more data is collected to make smarter recommendations — and keep you listening.
At this talk, you'll learn from industry experts who have mastered the art of using data to deliver an exciting and unique experience of music en masse. You'll walk away with a better understanding of where data is taking the future of music, how data is empowering artists as well as listeners, and how Spotify uses data to personalize your Discover Weekly playlist.
Product Owner, Recommendations and Personalization,
Michelle currently works at Spotify as the Product Owner of the Recommendations and Personalization Platform. She leads a cross-functional team of back-end and machine learning engineers focused on improving the recommendations that power many of the surfaces of Spotify; these include the popular playlists such as “Discover Weekly” and “Daily Mix” as well as features such as Search and Home. Prior to joining Spotify, Michelle spent 2.5 years at KAYAK as the Head of Product for Hotels, where she owned cross-platform product development for the end-to-end user journey from Search to Purchase. She has a passion for design, user experience, and machine learning, specifically as they relate to improving search, discovery and personalization.
I'm a Research Scientist at Spotify. Currently, I work on building a better podcast recommendation experience. My previous work at Spotify has focused on how users engage with the platform through voice search. I worked with ML, HCI and engineering teams to develop systems and experiences that respond to (voice) searches that either don’t have an obviously right answer (“Play guacamole making music”) or have millions of potential right answers (“Play music”).
I have a PhD in Linguistics from MIT and am broadly interested in how to represent and understand language as a computational system. I'm particularly interested in the spaces where linguistics and computer science overlap, including questions about how humans and computers can use natural language to communicate with one another.
Hagar currently works at Spotify as a data engineer. She builds products that connect artists and their fans, such as the Fans First program which presents fans with offers for unique artist experiences. Prior to joining Spotify, Hagar worked at different marketing companies building email marketing and fraud prevention tools, with a focus on data science and engineering.
We understand that, sometimes, plans change. If you can no longer make it to a class or workshop, please email us at least 7 days before the scheduled event date. No refunds will be given to cancellations made within a week of the class or workshop.
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