Meta Data Science interview questions

A recruited reached out to me and I had a call with her. This was followed by a technical screening with a data science manager. The last step was a full round of interviews onsite.

Recruiter conversation and phone screen, one phone screen via video call. At first I was pleased because the recruiter sent a detailed preparation guide and I had a few weeks to prepare. I spent some time preparing nearly every day, making sure I was well versed in R, which was the language that I requested for the phone screen. The recruiter emphasized that product sense was important, so I spent time thinking and reading about metrics necessary to evaluate products and how that may be applied to Facebook. In the end, I think I would have been better off without the interview preparation guide, as it turned out to be completely misleading. The interview contained no probability questions, even though that was mentioned as part of it, and no product sense questions. There was only one fairly straightforward data engineering type question. The rest was simply SQL questions, even though I had requested R as the language. I was able to use R to answer the SQL question, and then for the second follow-up questions switched to SQL, but really the type of question would be best answered with SQL. The interview guide said that if you requested R, then they would be testing dplyr/apply functions, but that wasn't really true. The SQL question was not straightforward, but fairly challenging. I was thrown off because I was expecting a data analysis question using R, and I was a bit nervous under pressure. I was able to answer the questions, but not without stumbling a bit. The whole process was frustrating because I write fairly complex SQL questions often as part of my job, and have never had a query I couldn't figure out. But under the pressure of the interview, I didn't perform spectacularly. I wish I had not spent time on the other parts of the interview prep and just focused on SQL, and I probably would have been more successful. So beware the prep guide may lead you astray.