Data Science at Spotify with Boxun Zhang

boxun-zhang

“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

Sponsors

Hired.com is the job marketplace for software engineers. Go to hired.com/softwareengineeringdaily to get a $2000 bonus upon landing a job through Hired.

Digital Ocean is the simplest cloud hosting provider. Use promo code SEDAILY for $10 in free credit.

Comments