Initial phone screen with a recruiter followed by a 45 minute phone call with another Data Scientist.
The Data Scientist I interviewed with was clearly another cog in the machine. He had quite a bit of an ego and his responses betrayed the fact that he is clearly into the little office political games behind played back at the headquarters. This is not a good look for the company or its culture. I don't care about your "internal baseball", as the interviewer put it.
The questions were fair but the attitude the interviewer gave at every step of the way was a huge turn off. There's no need to be smug or smirk at every answer being given. All sorts of red flags and alarm bells were going off in my head.
I've since interviewed with other companies who are a bit more empathetic during the interview process.
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.