“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?
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