I applied online. The process took 4 weeks. I interviewed at Meta (Menlo Park, CA) in June 2016
Interview
The position Interviewed is not core data scientist team. I was told that this is a general data scientist hire. It means that the team which you will work for will only be determined by your willingness and the need of a product team after a training camp.
The experience of interviewing with Facebook is very positive. The entire process of interview consists of three steps:
1) HR screening: HR briefed on the job and interview process of this position; After screening, HR will provide a bunch of tips and preparation materials for the upcoming online technical interview. However, regardless the relaxed atmosphere, you should be prepared with your answers to some typical behavior questions asked by HR;
2) online technical review: some data manipulation challenges (many similar questions can be found in other glassdoor reviews for the same position), online A/B experiment questions and short analytical questions (I was told that the pass rate of the round of interview is 1/5); From my standpoint, this online interview is mini-version of onsite interview by preliminarily assess the core skill set: statistics, analytical, data manipulation (R/Python/SQL) and product sense.
3) onsite interview: 2 sections on analytics (some reviewer called it product questions), 1 section on Math (not brain teasers), 1 section on technical (in-depth SQL data manipulation and interpretation of sample results; 2 section on SWE (whiteboard coding).
Interview questions [1]
Question 1
Due to NDA, I will not disclose the specific questions. However, most of the questions you can find in other reviews.
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.