Software Engineering Daily

Data Science at Spotify with Boxun Zhang

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“I normally try to sit together or very close to a product team or engineering team. And by doing so, I get very close to the source of all kinds of challenging problems.”

Spotify is a streaming music service that uses data science and machine learning to implement product features such as recommendation systems and music categorization, but also to answer internal questions.

Boxun Zhang is a data scientist at Spotify where he focuses on understanding user behavior within the product.

Questions
  • What is the overlap between distributed systems and data science?
  • How has Spotify’s big data architecture evolved over time?
  • As a data scientist do you need to understand this big data architecture well?
  • What were the benefits for starting to use Kafka?
  • What kinds of data science problems do you tackle at Spotify?
  • Could you describe what a random forest is?
  • Why are there so many streaming systems, and what do you use at Spotify?
  • How will data science change moving towards the future?
    • Links
    • The Evolution of Big Data at Spotify
    • Luigi
    • Project Jupyter
    • XGBoost
    • Automatic Statistician
    • Skytree
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