Here at SoundCloud, we’ve been working on helping our Data Scientists be more effective, happy, and productive. We revamped our organizational structure, clearly defined the role of a Data Scientist and a Data Engineer, introduced working groups to solve common problems (like this), and positioned ourselves to do incredible work! Most recently, we started thinking about the work that a Data Scientist does, and how best to describe and share the process that we use to work on a business problem. Based on the experiences of our Data Scientists, we distilled a set of steps, tips and general guidance representing the best practices that we collectively know of and agree to as a community of practitioners.
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October 4th, 2017 Data Science Machine Learning Analytics Data SoundCloud's Data Science Process By Josh Devins
June 21st, 2016 Announcements Recommendation System Machine Learning Data Science Can a machine surprise you? We believe so. By Nicola Bortignon
With more than 125 million tracks from over 12 million creators heard each month on our platform, SoundCloud is uniquely positioned to offer listeners a full spectrum of music discovery.
Classic hits, the latest releases, gems from underground talent and the best of what’s up-and-coming – all in one place.
How can you make great content discoverable and available at ease? How can you create a unique experience for every single user?