I will not be giving out any specific questions.Like all other companies the hiring process starts with a call from the HR. I was scheduled then for a phone interview a week out. Since I was applying for a data science/machine learning role I was asked questions on probability. Keep a calculator by your side since they expect you to give the final answer not just the formula. The question was not very hard but solving math problems over the phone is never easy. My suggestion would be to practice a few probability questions and revise basic probability theory (Khan Academy helped me a lot). The second phone interview happened in another 2 weeks. This was a basic computer science interview. Some questions about linux (basic stuff like grep, ls etc). If you have worked with linux for a while this should be easy. He then moved on to a basic mapreduce question. It was a very simple question and a basic knowledge about mapreduce will do it. The third round is a coding challenge. They gave me with a small data set and I had to answer a few questions on that data set. Having a background in mysql will be helpful since a lot of the questions can be answered by doing simple sql queries. They generally give you a weekend to solve the coding challenge. Once that was done I was invited for an onsite interview. The onsite interview had a behavioral section, case study and general machine learning. Behavioral Section (2 interviews) is questions like Tell me a time when .... Capital One gave some example questions. You can find a lot of them on the internet and on Capital One's website. Having a few answers/incidents in mind is helpful. Try not to make up stuff. Case Study (2 interviews). These are also available on Capital One's website. It's doing some amount of simple math (mostly algebra). They did ask me to draw a bunch of graphs for break even analysis. If you are decent at math, this is not very hard, so just keep your cool. The first case study was very easy, the second one was a little bit more challenging but not difficult. Essentially if you were having this conversation in a bar and not in an interview setting it would not be a problem at all. So just remain calm and work through the problem and ask a lot of questions. Make sure you have all the data before you proceed with the solution. Verify each step of your solution with the interviewer. Make sure you check your arithmetic. Machine Learning (1-2 interviews). Basic stuff about NN, Regression and Decision Trees. I have been doing machine learning for a while so this interview was the easiest. If you relatively new to machine learning I would suggest going through Andrew Ng's course on coursera. There are also many machine learning classes on youtube. The one that I prefer the most is by Prof. Abu Mustafa from caltech. The interviewers are very nice and friendly. They are there to help you and the overall experience was great. They also take you out for lunch. Thats a good time to relax and ask some informal questions. They also give 10-15 breaks between some interviews. It will be a long day (mine was from 8am-4:30pm) so be mentally prepared. I watched soccer videos in the 15 minute break that helped me relax a lot. At the end of the day I think if you keep calm you will get through the interview. Don't be afraid to say "I don't know" to questions that you don't have a clue about. The interviewers do not expect you to know everything. It's a much better idea to admit that you don't know rather than saying something stupid. I said "I don't know" to a few questions and that worked in my favor as the interviewer thought I was a humble person. Good Luck