5 stage interview process: Stage 1 involved talking with the recruiter and checking off some basic eligibility criteria. I had a little bit of time with the recruiter to talk through some basic questions. Stage 2 involved talking with a senior data scientist on the team and answering a handful of technical questions related to data science and machine learning. Nothing too taxing in this round if you know your stuff. Again I had some time to ask some questions about the team. Stage 3 involved a 1-hour live programming task, where I analyzed a dataset with my language of choice with the hiring manager and 2 other team members watching live. The task went from data ingestion to posing a problem and then implementing it as a ML problem. For this stage, you'll want to make sure that you're plenty familiar with your data science ecosystem -- although they do allow you to use Google and documentation. Stage 4 involved the same group in Stage 3 and we talked through a business problem and how I would approach it from conception to implementation. This stage is meant to test how effectively you think as a data scientist and can take nebulous problems and turn them into data science problems. Stage 5 involved a talk with just the hiring manager to answer any remaining questions I had about the role. The recruiter and hiring manager were quite responsive during the whole interview process, and they made an outstanding and competitive offer at the end of the interview process. DataRobot is recruiting aggressively right now and it shows through their streamlined process. Overall it was a quick interview process (about 1 week) and I felt that the interviewers were quite respectful of my time. The interviewers even asked for feedback on how to improve the interview process, which speaks to their focus on respecting their interviewers' time and streamlining the interview process.