First interview was over the phone with the recruiter with more general questions, like general experience, salary, etc. He gave more info about the job and if both of you are still interested, then he moves you forward. Lasted about 20-30 min. 2nd interview was with the hiring manager over the phone. Asked some questions about my experience, and then did a long case study question. I don't remember the exact question but it was just some sort of hypothetical project related to real estate and you discuss with them, in a conversational way, how you would plan to accomplish this using statistics and data science. Interview lasted about 1 hour. 3rd interview was with 5 different people, 1 hour each, so 5 1/2 hours total including lunch break. Because of covid, it was over Zoom, but I think this interview is normally intended to be onsite. 2 of the interviews were with managers from other data science teams, one was with the head of all data science teams, and 2 were with senior data scientists. The interviews with the managers were mostly behavioral questions and case studies. One case study that I've heard is used frequently there is like this: if you worked for google and had to improve google maps, what would you do? This one is very conversational as well, and was more business-oriented as opposed to technical. Then the interviews with the 2 senior data scientists were very technical. One of them was an assessment in R, and the other was a few assessments in SQL. Not really data science specific for the R one. The R question, for example, was: if you have 2 rectangles and you're given the x and y coordinates of each, write a function that returns whether the rectangles overlap. Highly unlikely that they will use the same question, but that's a general idea of the kind of coding question they would ask. Business skills are very important for this job. I learned firsthand that having flawless techncial skills is not enough.