I applied through a recruiter. The process took 3 weeks. I interviewed at Meta (Menlo Park, CA) in Feb 2015
Interview
Interview process is long and drawn out. As expected, of course, for large tech companies these days. Unfortunately, data science interviews do not necessarily reflect the ability of applicants to do the job they are applying for, and do not reflect a normal day's work. More challenging questions about coding than would make sense for anyone with an analysis/stats background. Instead difficult questions should be focused on problem solving skills
Interview questions [1]
Question 1
Write a sorting algorithm for a numerical dataset in Python.
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.
I applied online. The process took 6 months. I interviewed at Meta
Interview
Completed 3 rounds of the process, which includes the initial recruiter screen, technical, full loop, and team matching.
Couldn't move past the full loop interview. The interview was very engaging, and I actually enjoyed working through the cases. No crazy questions.
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