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      Recherches associées: Avis sur Amazon | Offres d’emploi chez Amazon | Salaires chez Amazon | Avantages sociaux chez Amazon
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      Entretien pour Data Scientist

      26 déc. 2020
      Employé (anonyme)
      Seattle, WA
      Offre acceptée
      Expérience positive
      Entretien moyen

      Candidature

      J'ai postulé via la recommandation d'un employé. J'ai passé un entretien chez Amazon (Seattle, WA) en sept. 2020

      Entretien

      Hey, guys writing this out coz I’ve used glassdoor so much to get a sense of what to prep. Thanks for the posts and here’s to paying it forward :) Applied with Referral, the first time I did not get picked up, applied again with another colleague, and got a call the next day! The recruiter reached out and asked me a time for a phone screen I took a date 2 weeks out. Had two phone interviews, and 5 onsite interviews later. All interviews had a common theme - a mix of technical and LP questions. Some interviews were more towards LPs and others were more towards technical. Regarding LPs, I’d say prepare solid stories, write them down, and even practice them with your friends. Make the stories diverse, talk about stories from different company experiences, do not repeat stories from one particular company, it’ll undermine your years of experience. I did that and was given L4 even though I applied for L5. Regarding Technical questions, questions were regarding: Machine Learning -- ML system design(given a business problem, design the architecture from start to end output), Explain inner workings of Tree-based methods and Random Forest in detail, Regularization general idea why and when to use, L1 vs L2, explaining PCA in details with multiple use based cross-questions, code up gradient descent in python, among other questions. Stats: A/B testing, hypothesis testing, end-to-end A/B test design for a business problem, a bunch of random stats questions, time-series overview of ARIMA, and applying to the business case above, among other questions... All cross-questions were such that they pushed me towards going into more and more detail of the topics, they want to understand they I knew things properly.

      Questions d'entretien [1]

      Question 1

      Wrote high-level question areas above.
      Répondre à cette question
      27

      Autres retours d’entretien d’embauche pour un poste comme Data Scientist chez Amazon

      Entretien pour Data Scientist

      1 juin 2026
      Candidat à l'entretien anonyme
      Seattle, WA
      Aucune offre
      Expérience positive
      Entretien moyen

      Candidature

      J'ai passé un entretien chez Amazon (Seattle, WA)

      Entretien

      There are three rounds in total. The process begins with a coding round, followed by the main interview loop, where you will meet the team and discuss technical skills, experience, and fit.

      Questions d'entretien [1]

      Question 1

      Basic ones in leetcode, checkout neetcode
      Répondre à cette question

      Entretien pour Data Scientist

      21 mai 2026
      Candidat à l'entretien anonyme
      Aucune offre
      Expérience neutre
      Entretien difficile

      Candidature

      J'ai passé un entretien chez Amazon

      Entretien

      First round is fun, second round, which is also the final round involved 5 sessions, with different focus. For some sessions, not be able to present my story completely, time was tight, and interviewers were rushing.

      Questions d'entretien [1]

      Question 1

      Bias in regressions, how you would resolve them
      Répondre à cette question

      Entretien pour Data Scientist

      6 mai 2026
      Employé (anonyme)
      Offre acceptée
      Expérience positive
      Entretien difficile

      Candidature

      J'ai passé un entretien chez Amazon

      Entretien

      Thrilled to have accepted the offer — the process was tougher than I expected. The first round was primarily technical, where I tackled an A/B testing design question that required detailed metrics and sample size calculations. Later, I faced a SQL query challenge focused on tracking customer purchases over consecutive months. Funny enough, I had spent quite some time on PracHub digging into similar case studies, which really helped me approach these problems confidently. The final round included behavioral questions, and I felt well-prepared overall.

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