I applied through an employee referral. The process took 6 weeks. I interviewed at Meta in Sep 2021
Interview
Started with one 30 min phone call with a recruiter - mostly a conversation about motivations and next steps.
Next stage was an initial screening interview with a Data Scientist. This was a light version of the on-site interviews where they asked one SQL question and one product case question. Dug deep into the product question to ensure good product acumen.
On-site was virtual and consisted of 4 30 min interviews with Data Scientists. Interviews were: Maths/Stats, SQL, Analytical interpretation and Product case study
Interview questions [1]
Question 1
- How would you determine the health of FB Groups?
- How would you build a 'restaurants you may like' recommender system on the news feed
- Bayes Theorem stats question
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