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      Ricerche correlate: Recensioni su Amazon | Offerte di lavoro di Amazon | Stipendi di Amazon | Benefit di Amazon
      Colloqui di AmazonColloqui per Data Scientist presso AmazonColloquio di Amazon


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      Colloquio per Data Scientist

      26 dic 2020
      Dipendente anonimo
      Seattle, WA
      Offerta accettata
      Esperienza positiva
      Colloquio nella media

      Candidatura

      Ho presentato la mia candidatura tramite segnalazione di un dipendente. Ho sostenuto un colloquio presso Amazon (Seattle, WA) nel mese di set 2020

      Colloquio

      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.

      Domande di colloquio [1]

      Domanda 1

      Wrote high-level question areas above.
      Rispondi alla domanda
      27

      Altre recensioni di colloqui per Data Scientist presso Amazon

      Colloquio per Data Scientist

      1 giu 2026
      Candidato anonimo a colloquio
      Seattle, WA
      Nessuna offerta
      Esperienza positiva
      Colloquio nella media

      Candidatura

      Ho sostenuto un colloquio presso Amazon (Seattle, WA)

      Colloquio

      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.

      Domande di colloquio [1]

      Domanda 1

      Basic ones in leetcode, checkout neetcode
      Rispondi alla domanda

      Colloquio per Data Scientist

      21 mag 2026
      Candidato anonimo a colloquio
      Nessuna offerta
      Esperienza neutra
      Colloquio difficile

      Candidatura

      Ho sostenuto un colloquio presso Amazon

      Colloquio

      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.

      Domande di colloquio [1]

      Domanda 1

      Bias in regressions, how you would resolve them
      Rispondi alla domanda

      Colloquio per Data Scientist

      6 mag 2026
      Dipendente anonimo
      Offerta accettata
      Esperienza positiva
      Colloquio difficile

      Candidatura

      Ho sostenuto un colloquio presso Amazon

      Colloquio

      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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