I was not a Data Scientist at Evernote, but I did get the pleasure of working with the Data Science/Augmented Intelligence team for my many years there.
Their team was, during my tenure, relatively small, but always working on extremely interesting projects. When some team decided they wanted a new feature, it was their responsibility to come up with how to do it and then make “the magic happen” behind the scenes.
In addition to that, they were (are) constantly coming up with newer, faster, better ways to accomplish existing subroutines. It was always fascinating to talk to members of the team about the coordinated rollouts they would be doing at the end of a long project, only to obsolete it and get ready to start all over again because something new had been discovered since the beginning of the project that would save another few microseconds of server time.
It is not a 9-5 job, but I can’t think of any that are in a startup.
“At the AI Evernote team the challenge is how does one develop algorithms for a user who has just 10 notes or a user who has thousands of notes, in that case how do we scale our intelligent offerings for different sets of data. So at Evernote we don “t have one big data problem but a 100 million smaller data problems, which is quite challenging.”1
For more information, the team occasionally posts at Evernote Tech Blog – The Care and Feeding of Elephants .
Originally Posted: https://www.quora.com/What-is-it-like-to-be-a-data-scientist-at-Evernote
Originally Posted On: 2015-02-03