I applied through an employee referral. The process took 2 weeks. I interviewed at Meta (Seattle, WA) in Nov 2019
Interview
Good: Recruiter gives you a lot of material to prepare for the interview (such as SQL).
Bad: The interviewer is incompetent as a senior data scientist. Seems like they ask questions from a question bank and only look for the exact solutions to the way that they know how to solve it. My solution was correct (and more efficient than the recruiters'), but she kept emphasizing on answering it the way that she knew.
Interview questions [1]
Question 1
SQL questions with aggregate functions and involving two tables/subqueries/pivoting data
Conversation with recruiter in email. Technical screening round where they ask about SQL and product sense. Onsite-Loop with four rounds. They ask about SQL, Product Sense, Statistics, Behavioural questions. The difficulty is average.
The technical round kicked off with a design question about A/B testing for Facebook Reels, which I found engaging. Then, I tackled a SQL query on user comments and how to account for novelty effects in ongoing experiments. Thankfully, I had prepared with the company-specific questions on PracHub, and it made a real difference in my confidence. The entire process felt smooth, and after some behavioral questions, I received an offer that I happily accepted.
Interview questions [3]
Question 1
Design an A/B test for a Facebook Reels ranking change and describe how you would interpret the results
Total 7 rounds: first round for resume screening, second for technical screening, then for on-site virtual with 4 interviews back to back, then hiring manager round after team matching and then salary negotiation with HR
Interview questions [1]
Question 1
Meta’s evaluation rubrics focus heavily on "Product Thinking over Fancy Math". Interviewers want to see if you can operate like a product owner with an analytical mindset, navigating messy scenarios affecting billions of users