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      Búsquedas relacionadas: Evaluaciones de Meta | Empleos en Meta | Sueldos en Meta | Prestaciones en Meta
      Entrevistas en MetaEntrevistas para el cargo de Data Scientist en MetaEntrevista en Meta


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      Entrevista para Data Scientist

      12 jul 2017
      Candidato de entrevista anónimo
      Menlo Park, CA
      Sin ofertas
      Experiencia neutra
      Entrevista promedio

      Solicitud

      Me postulé a través de una recomendación de un empleado. Acudí a una entrevista en Meta (Menlo Park, CA) en jul 2017

      Entrevista

      Had a phone screen with a recruiter that led to a video interview. Video interview covered building models to solve specific FB problems (are people connected/not), some ML, feature engineering, identifying pitfalls in a model and data leakage, also covered some SQL (though I was given the option to use Python as well). Onsite interview was a series of five interviews broken up by lunch with a DS, and a brief meet and greet in the morning. The topics where mostly focused on product analysis and A/B testing (if we have a product and see some trend in different users make a hypothesis about why we see that trend and test it). One interview was probability and data focused with a couple college level probability questions. One interview was focused on data manipulation in the language of my choice. And the last interview was SWE with a CS type algorithm development problem. Overall, I would say that a great deal of the interviews did not focus on what I (as a working Data Scientist) do on a daily basis, which is primarily building ML models. There was a definite bias towards A/B testing and almost all of the interviewers brought in situational product based questions. During lunch the DS I was with was very open and forthcoming about what working at Facebook is like and the types of problems they tackle on the job. He was also very frank about the lack of ML work done by DS's at Facebook and basically said they have one of the best ML engineers in the world working there and he built a suite of tools that are better than anything you will build, ever. As far as his interaction with ML went, he just collected the data he needed and passed it into one of these tools. In the end I did not receive an offer, though I was provided some vague feedback. My technical skills where very strong, but product awareness and analysis ended up hurting me. Full disclosure I do not have/use Facebook or Instagram and though I disclosed this before beginning the process I felt that it had an impact on my interviews.

      Preguntas de entrevista [2]

      Pregunta 1

      We have a product that is getting used differently by two different groups. What is your hypothesis about why and how would you go about testing it?
      4 respuestas

      Pregunta 2

      Given a specific product, come up with some potential improvements and design a series of experiments for testing/implementing these changes.
      Responder pregunta
      21

      Otras evaluaciones sobre las entrevistas para el cargo de Data Scientist en Meta

      Entrevista para Data Scientist

      19 jun 2026
      Empleado anónimo
      Oferta aceptada
      Experiencia neutra
      Entrevista difícil

      Solicitud

      Acudí a una entrevista en Meta

      Entrevista

      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.

      Preguntas de entrevista [1]

      Pregunta 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.
      Responder pregunta

      Entrevista para Data Scientist

      11 jun 2026
      Empleado anónimo
      Cambridge, MA
      Oferta aceptada
      Experiencia positiva
      Entrevista difícil

      Solicitud

      Acudí a una entrevista en 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

      Preguntas de entrevista [1]

      Pregunta 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
      Responder pregunta

      Entrevista para Data Scientist

      23 may 2026
      Empleado anónimo
      Menlo Park, CA
      Oferta aceptada
      Experiencia neutra
      Entrevista difícil

      Solicitud

      Acudí a una entrevista en Meta (Menlo Park, CA)

      Entrevista

      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

      Preguntas de entrevista [1]

      Pregunta 1

      Questions on Bayes Theorem, Probability distribution, etc.
      Responder pregunta

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