Hi, I am preparing for an onsite interview with FB for a Data Science, analytics role. In one of the interviews, you are given an open-ended question, and your task is to translate it to a structured data question and showcase your analytical¯ approach. A toy example is "Do siblings interact more or less on Facebook?". To solve that, one could think of 1) how to detect siblings, 2) how to quantify interactions 2) how to split the data (e.g., region, age) to provide actionable insight. What else could the interviewer expect?
Are there more examples like this that anyone could share? Is there anyone who could evaluate the responses to such questions and highlight things that the interviewers expect that may not be assumed? #facebookdatascientist #facebookinterview #facebookanalytics
That said, for the role, think "Data driven decision making". This means you should be able to synthesize situations into data problems and propose a solution. To prepare, just go through a number of situations. Knowing sql alone isn't going to do shit for you. Also make sure you know basic statistics - distributions, testing etc..
Also, contrary to popular belief you don't need to do your interview in sql, you can do it in python or R - people often choose sql because it takes the coding out of it and the focus remains the business understanding of the problems and your data science skills.
Don't understand the hatred on blind, but neither Facebook nor people in the role are idiots - and Facebook as a company certainly doesn't pay 400k salaries to people for running sql queries - its all about driving better, more data driven decisions.