Candidatei-me por meio de recrutador(a). O processo levou 6 semanas. Fui entrevistado pela Meta em jun. de 2018
Entrevista
A recruiter and a technical sourcer outlined the entire process for me upfront in an initial phone call. Then I had multiple phone screens, but ultimately, I did not move on to an onsite interview.
Although their interview was difficult, I appreciate that they were highly interested in my profile and tried to fill multiple positions with my resume, starting with senior data scientist. This has guided my journey and informed my choices towards what skills I acquire in my current role. For that, I rate this as high of an experience as possible without getting an offer.
Fiz uma entrevista na empresa Meta (Menlo Park, CA).
Entrevista
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.
Perguntas de entrevista [3]
Pergunta 1
Design an A/B test for a Facebook Reels ranking change and describe how you would interpret the results
Fiz uma entrevista na empresa Meta (Cambridge, MA).
Entrevista
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
Perguntas de entrevista [1]
Pergunta 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