The interviews, as I recall: (1) Someone from finance department, covering collaboration w/ members outside of the core group. (2) Hiring manager asked questions around behavioral and problem solving approach; critical thinking; fit for team and group. (3) Product manager asked questions on product intuition and product impact. Being able to connect the problems you’re solving back to the business. Are you able to communicate with a non-technical audience. Some questions about metrics. (4) Coding -- one data manipulation question using Python or R. Could have used SQL to answer it as well. One algorithm/data structure question which honestly isn't really relevant to what someone w/ a statistical modeling background does, but seems to be included these days nonetheless. (5) Data science interview -- met with data scientist team leader who asked questions regarding how to define a given data science problem, what kind of metrics to use, models you'd consider using to answer such questions, etc. Some of the questions were experimental in nature, others were more machine-learning-esque. Of the latter category, would have been beneficial to at least be aware of online learning techniques and perhaps some time series models given the temporal nature of the data. (6) Interview with person not on the same team as the group I interviewed with. This person was supposed to ask me to explain my research and projects and experience according to the recruiter, but wound up just asking me questions about their own work, unexpectedly.

Expected value for a dice problem and a case study about a Uber problem