Data Scientist Product applicants have rated the interview process at Meta with 3.2 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 50% positive. To compare, the company-average is 56.6% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist Product roles take an average of 49 days to get hired, when considering 12 user submitted interviews for this role. To compare, the hiring process at Meta overall takes an average of 31 days.
Common stages of the interview process at Meta as a Data Scientist Product according to 12 Glassdoor interviews include:
Phone interview: 32%
One on one interview: 24%
Skills test: 20%
Group panel interview: 8%
Background check: 8%
Presentation: 8%
Here are the most commonly searched roles for interview reports -
I applied through an employee referral. The process took 3 weeks. I interviewed at Meta (London, England) in Aug 2016
Interview
Two Phone screens, than on-site in London. Phone screen with technical interviewers. On-site interviews both technical interviewers and management. The process was very well organized and I received a very detailed feedback afterwards.
I applied online. I interviewed at Meta in Jun 2025
Interview
It kicked off with an initial phone screen that jumped straight into technical questions, so you really have to be warmed up—especially on A/B testing: framing the hypothesis, picking primary metrics and guardrails, walking through power/MDE, exposure and unit of randomization.
Interview questions [1]
Question 1
Walk me end-to-end through how you’d run an A/B test for a new feature—start by selecting decision-driven metrics.
I applied online. I interviewed at Meta (Menlo Park, CA) in Mar 2025
Interview
30 min call with recruiter, 1 hour Zoom interview based around product case and SQL/Python database questions. The final round is a loop interview. Two business case interviews, two technical interviews.
Interview questions [1]
Question 1
Please solve this technical question using either R, Python, or SQL. If given a new feature, how would you measure its success rate in an area? If we added another featur,e how would that impact your original measurement.
Meta's SQL screening tests query skills, optimization, and handling complex datasets. The case round evaluates problem-solving, business insights, and technical solutions to real-world scenarios using data-driven approaches. Its moderate difficulty