I applied through a recruiter. The process took 3 months. I interviewed at Meta (Menlo Park, CA) in Mar 2019
Interview
Recruiter reached out to scout for interest - he was extremely helpful, informative, and encouraged me to take my time to prepare with thorough material. FB wants you to be as prepared as possible with no surprises/tricks to the interview to pick out those who are not only the most qualified but also the best prepared. Scheduled the initial interview around ~2.5 months out.
Video Interview - 45 minutes with a Data Scientist. He opened with a quick rundown of my background and why I want to work for Facebook, but the bulk of the interview was technical - the first half being SQL on Coderpad and the second being product interpretation. I passed and received confirmation that I would advance to the onsite on the same day.
On Site Interview - 4 30-minute rounds testing various topics surrounding applied data, product sense, probability & statistics, and SQL (or Python/R), with a 45 minute lunch in between with a data scientist who is there to help you answer any questions (not part of the interview. Zero questions on behavioral or anything regarding my background. I was not extended an offer and was communicated the rejection shortly after.
Overall, a very pleasant experience - FB is a top notch company with best practices, though of course, individual experience can and will widely vary. For on-site, it's very important that you map and diagram your thoughts on the white board. Most questions appear as though there is a specific answer in mind that they are looking for, though the way you get there might be flexible. The best way to prepare is to think through the different scenarios and products and figure out a way to build a business case around measuring some metric or improving the product. Expect lots of pushback with detailed, probing questions during your answers.
Interview questions [3]
Question 1
Suppose FB wants to launch feature X on product Y - how would you assess whether or not this is a good idea? How about when standard AB Testing does not work?
Given a table of users, dates, statuses, etc. - calculate the ratio X grouped by Y on day Z. Call out edge cases - don't assume anything about the data without clarifying.
Given a scenario X - figure out the probability of A, probability of A given B, etc. Draw out the distribution of users in scenario Y - figure out what the mean, median, and xth percentile is.
Conversation with recruiter in email. Technical screening round where they ask about SQL and product sense. Onsite-Loop with four rounds. They ask about SQL, Product Sense, Statistics, Behavioural questions. The difficulty is average.
The technical round kicked off with a design question about A/B testing for Facebook Reels, which I found engaging. Then, I tackled a SQL query on user comments and how to account for novelty effects in ongoing experiments. Thankfully, I had prepared with the company-specific questions on PracHub, and it made a real difference in my confidence. The entire process felt smooth, and after some behavioral questions, I received an offer that I happily accepted.
Interview questions [3]
Question 1
Design an A/B test for a Facebook Reels ranking change and describe how you would interpret the results
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