Capital One Data Science interview questions

Very professional and clearly laid out process. The data scientist interview comprises of 4 stages. Stage 1 is a coding test using Hackerrank and you have about 2.5 hours to complete it. Stage 2 is a phone interview - partly behavioral and partly technical thinking. Stage 3 is a data science challenge to showcase your data munging and analysis skills. The 4th stage is series of 7-8 one-one interviews comprising of case studies and behavioral interviews. This job was for the Capital one labs. The people seem to be really nice and professional. The HR was very systematic and helpful in keeping you updated. The only thing is that although a startup within a big firm they seem to have the problem of a large firm. Also, they seem to test you on many technology seems like they are not used and a bit unclear as to what I will be doing once I get the offer. Overall great experience and very good interview process for a large firm. Had a better offer so did not accept offer.

I was contacted by a recruiter in March to submit an application. The process was similar as described in some of the newer posts: there are 3 rounds before the on-site interview: first a HackerRank online coding test, then a technical phone screen by a data scientist, lastly a data analysis coding challenge containing a small machine learning question and a larger data analysis question. The bar in those 3 rounds were not very high and you likely would pass by not getting all the correct answers. I for one didn't get full credit for the HackerRank test. I think I did pretty well on the phone screen(the interviewer told me on the spot that I passed) and the coding challenge (recruiter said that the senior data scientist reviewing my work was "impressed"). But that's where my luck ended. The onsite interview was a full day, 6 sessions with 2 case interviews, 2 behavioral interviews and 2 job fit/technical interviews. The problems in the case interviews and the behavioral interviews were in line with what everybody else shared here. My performance was definitely not perfect in any of them, but I was able to generally finish all the questions in time with minor assistance from the interviewers. The 4 interviewers in the mourning were all nice and encouraging. Where I failed miserably was the two technical interviews in the afternoon. I assumed that based on my work experiences as a data scientist I'd be asked about more practical problem-solving or machine-learning related problems, but both interviewers still gave me very stylized, hit-or-miss trick questions (one about string manipulation and one about dynamic programming. those you would find on technical interview books, but would rarely use in a real-world setting, especially as a Data Scientist) which is more suitable for software engineers and/or wall street quants. I'd probably do much better when I was still in school and can dedicate my time for interview-prep, but at this point I was severely exhausted (not given any rest between interviews) and shocked I basically gave up. Thinking back, I was probably too naive to think that my work experience has exempted me from brain teasers. As long as there are too many people applying for the job, those questions will always have their places as justifications to eliminate candidates. The attitude of the two interviewers in the afternoon was also a bit strange. The first interviewer spent the first 10 minutes of the interview to basically suggest that since I mainly used R and SQL for my current job, I will not be able to quickly pick up newer tools like Python, Hadoop, Scala, etc. The second interviewer spent his first 10 minutes suggesting that he had never heard of the small company I work for now and that my modeling approach has some obvious flaws. After the tone of the interview was set, my failure in the technical questions became nothing but self-fulfilling prophecies. During my conversation with them I indeed found out my background to not be a perfect fit for the position, and I think they probably know it before the interview. However, rather than communicating it as a plain mismatch of expectations, they acted in a manner that made me feel professionally inferior and thus very uncomfortable. It's overall a very informative process and I got a very interesting glimpse on how big data will strategically play into the daily operation of a very large company, and what big data technologies are currently in demand. I just don't understand how I was able to advance so deeply into the interview process with such a misalignment of qualifications (I did both my HackeRank test and my coding challenge in R, which was enough hint for them to reject me if the choice of data analysis tool is really important). It's a waste of everybody's time.