Data Scientist applicants have rated the interview process at Meta with 3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 100% positive. To compare, the company-average is 59% positive. This is according to Glassdoor user ratings.
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I applied through a recruiter. I interviewed at Meta
Interview
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.
Interview questions [1]
Question 1
They asked SQL questions, probability and product analysis
I applied through a recruiter. I interviewed at Meta in May 2017
Interview
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.
Interview questions [1]
Question 1
SQL question
One basic data engineering related question
I applied through a recruiter. I interviewed at Meta (Menlo Park, CA) in Apr 2017
Interview
The hiring process is very clear and well done. Each step of the way, recruiters will walk you through what their expectations are and provide you with sample questions.
You set your own schedule so you can make sure you have has much time to prepare as is necessary.
I think the key part is to come in with a good understanding of Facebook's line of products in terms of metrics, features, audience.
Interview questions [1]
Question 1
Building a histogram of post reply count in SQL (number of posts with x replies, x+1 replies, etc).
Building a table with a summary of feature usage per user every day (keep track of the last action by user and roll that up every day).
Basic conditional probabilities (check out brilliant.org for their source of inspiration)