I applied through an employee referral. The process took 4 weeks. I interviewed at Meta (Menlo Park, CA) in Jan 2018
Interview
Applied for the new grad position through referral. 1 month. HR phone screen followed by Tech phone screen (SQL and problem solving), Onsite (4 rounds - SQL, Prob & Stats, Problem solving, Product Interpretation). SQL questions are really easy and basic. Technical section was really easy but product based rounds were difficult.
Interview questions [3]
Question 1
1. FB has hired raters to rate ads. 80% are careful rates and rate 60% of the ads as good and 40% as bad, 20% are lazy raters and rate 100% ads as good. What is the probability that an ad is rated good? Given that 3 ads have been rated as good, what is the probability that they were rated by a lazy rater? Given that n ads have been rated as good, what is the probability that they were rated by a lazy rater? You want to classify raters as careful/lazy, how would you do that using all the probabilities and ideas discussed above (open ended question)?
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.
