The recruiter contacted me via linkdin and set up a phone interview with one of the data scientists in facebook. It was supposed to be 45 minutes and the recruiter had already sent out a detailed email of what to expect. The interview began with a sql coding qs , followed by A/B test questions and how to track decrease/increase of metrics.
I was able to answer each one of them but the interviewer seemed hardly interested and there were no follow up questions as if he didn't find me worthy of engaging in any conversation. My overall experience was bad and I could have cleared the interview had there been a better guy with more experience and understanding of how interviews are conducted.
Interview questions [3]
Question 1
Write a sql query to find out the overall friend acceptance rate for a given date?
Table :- User_id_who_sent|User_id_to_whom|date|Action (Sent, accepted, rejected etc)
Tough interview overall—definitely not what I expected. The technical rounds were intense, particularly when they had me design an A/B test for the News Feed ranking algorithm. I had to discuss metrics and sample sizes in detail. Lucky for me, the time I spent on PracHub right before the interview helped me nail that deep-dive question as it mirrored what I practiced. The behavioral questions felt standard but were still challenging. After a whirlwind process, they extended an offer, which I happily accepted.
Interview questions [1]
Question 1
Design an A/B test to evaluate a new ranking algorithm for the Facebook News Feed. Walk through metric selection (engagement, time-spent, MSI, well-being), unit of randomization given network effects between friends, sample size and power calculations, how you'd detect novelty effects vs. true lift, and how you'd handle a guardrail metric regressing while the primary metric is up.
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
The Interview Process is very structured -
First Tech Screening round - 45 mins (usually can extend a bit depending on the interviewer)
- 2 SQL Questions ( Medium to Hard ) - based on Joins
Full Loop - 4 rounds 45 mins each.
- SQL
- Behavioral
- Analytical Execution - stats & prob, A/B testing, case study
- Analytical Reasoning - Case study
Interview questions [1]
Question 1
Questions on Bayes Theorem, Probability distribution, etc.
