Meta Data Scientist interview questions

My resume was entered into the system by a friend who currently works there, but after a week and no contact, I applied online to a Data Scientist position. Data scientists at Facebook have a totally separate hiring process from software engineers. You have an initial phone screen by a data scientist which will focus on your 'analytical ability.' For those of you who (like me) have no idea what that means, it means a tiny bit of coding/scripting in a language of your choice while you work a reasonable, made-up data science scenario. They'll give you pretend access to a pretend database of information, have you write a few queries, give you fake data for your output, and have you debug plausible scenarios for that fake data. I received word rather quickly (two days later) that I passed the phone screen and would be invited to Mountain View for a day of interviews. I scheduled those interviews for 3 weeks down the line. Interviews at Mountain View are grueling, not because of their technical difficulty, but rather because of the interview setup. I was interviewed in a tiny closed cubicle no more than 8 feet x 8 feet; room for two one-seater couches and a tiny table. The wall was a whiteboard. There were 5 back to back 30 minute interviews, and while the interviewers were apparently supposed to ask if I needed water or a bathroom break, they often forgot to do so. The next interviewer was waiting right outside when the last interview ended. After we covered all of the technical content (about which I signed an NDA, so I unfortunately will not share the details of that), I had about 120 seconds to quiz my interviewer about what data science is like at Facebook. I may have earned brownie points with one on-site interviewer for stopping him when he started asking me the same question that I had had during my phone screen. He thanked me and changed to a new problem. I studied for the Data Scientist interviews by: a) coding in python (which I do for my job; they were happy to let me code in python for the on-site interviews) b) reviewing Stanford's online statistics 101 class c) doing a few 'hat trick' type probability puzzles I was well prepared for their interview questions. I heard back from my recruiter 1 week after on-site interviews and received a generous offer with a fungible 2-week acceptance deadline.

This was a very long process. However the recruitment team was extremely helpful in keeping me completely informed at every step of the way (a huge plus). As a disclaimer, coming from years of working in academic settings I have no point of comparison. These are just my personal impressions. I was introduced to a recruiter after one of our students started working at Facebook. He was very prompt in getting back to me and setting up a phone call. He then passed my resume to another recruiter (closer to my area of expertise). Over the next few weeks, I had a number of phone conversations with different people (mostly analytic, coding and statistics type questions.) The recruiter working with me was very prompt in touching base with me after each interview, telling me how they felt about the interview and getting my feedback on how I felt about it. After a few weeks they flew me to Menlo Park for an on site interview. The on site interview consisted of a series of five 30-minute interviews with project managers, data scientists and software engineers, all of whom were very engaging and interesting people. Talks were 1/4 about my current work, a bit less than 3/4 technical questions they expected me to work through, and a few minutes of time for my questions about the company, its people and processes. The recruiter reached out to me after the on site interview and scheduled two more phone interview, and an offer was made shortly after the last phone interview.