Interview questions from some interviewers were appropriate for fresh graduates, less so for people with real world experience. New grads will soon forget the details of much of what they learned at university but don't use regularly in their working role. They'll remember enough for a search query to find materials online when a quick refresher is needed, and that's all that matters. It's better to ask about details of related working experience. Coding portion given by someone wholly unfamiliar with the language being tested. Coding tasks were straight out of an introductory programming course in a low level language like C or C++, but not relevant to tasks common to a working data scientist, where high-level languages are the norm. There were no questions at all about the differences between working with small data, with which I have much experience, and big data, which eBay has, but with which I've rarely had the luxury of using. This is the primary difference between the role for which I was interviewing and my most recent role. I expected some questions. Surprisingly little was asked about machine learning or other data science related topics, which is where my strengths lie, and what is highlighted on my resume. Of the five interview sessions, there were only two in which we actually discussed things that were relevant to my skills, education, or anything else otherwise represented on my resume.