I applied through an employee referral. The process took 3 months. I interviewed at Meta (Mountain View, CA) in Jan 2014
Interview
My resume was entered into the system by a friend who currently works there, but after a week and no contact, I applied online to a Data Scientist position.
Data scientists at Facebook have a totally separate hiring process from software engineers.
You have an initial phone screen by a data scientist which will focus on your 'analytical ability.' For those of you who (like me) have no idea what that means, it means a tiny bit of coding/scripting in a language of your choice while you work a reasonable, made-up data science scenario. They'll give you pretend access to a pretend database of information, have you write a few queries, give you fake data for your output, and have you debug plausible scenarios for that fake data.
I received word rather quickly (two days later) that I passed the phone screen and would be invited to Mountain View for a day of interviews. I scheduled those interviews for 3 weeks down the line.
Interviews at Mountain View are grueling, not because of their technical difficulty, but rather because of the interview setup. I was interviewed in a tiny closed cubicle no more than 8 feet x 8 feet; room for two one-seater couches and a tiny table. The wall was a whiteboard. There were 5 back to back 30 minute interviews, and while the interviewers were apparently supposed to ask if I needed water or a bathroom break, they often forgot to do so. The next interviewer was waiting right outside when the last interview ended. After we covered all of the technical content (about which I signed an NDA, so I unfortunately will not share the details of that), I had about 120 seconds to quiz my interviewer about what data science is like at Facebook.
I may have earned brownie points with one on-site interviewer for stopping him when he started asking me the same question that I had had during my phone screen. He thanked me and changed to a new problem.
I studied for the Data Scientist interviews by:
a) coding in python (which I do for my job; they were happy to let me code in python for the on-site interviews)
b) reviewing Stanford's online statistics 101 class
c) doing a few 'hat trick' type probability puzzles
I was well prepared for their interview questions.
I heard back from my recruiter 1 week after on-site interviews and received a generous offer with a fungible 2-week acceptance deadline.
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.