J'ai postulé via un recruteur. Le processus a pris 2 semaines. J'ai passé un entretien chez Amazon (San Francisco, CA) en mai 2022
Entretien
Contacted by a recruiter, started with a normal recruiter phone screen. Advanced to a 1 hour online technical. The technical was given individually by a data engineer (not data scientist).
During the technical I was asked a relatively basic SQL question to pseudocode in a shared notebook type thing (The interview was through Amazon's Chime app). Despite informing the interviewer that I can eventually make SQL work, but I find the syntax inside out and upside down (and need an interpreter to check my syntax), he still insisted on smashing through this question instead of moving on to python (he did eventually let me solve the question using pandas pseudocode instead of SQL, after wasting at least 20 minutes where I was googling syntax and talking out my solution). Multiple times the interviewer effectively accused me of lying about "knowing SQL", even while I reminded him that I did not use SQL as a primary language, and that while I was capable with extended amounts of time and an actual interpreter, I was not presuming to be an expert. In the end we didn't even have time to go past the first python-type question (which I answered in 1/10th the amount of time as we wasted on the very-basic SQL question).
Icing on the cake, I received a rejection email on a Saturday evening, which I consider to be fairly unprofessional. At that point I expected to be rejected, but it still seems like information you should transmit at least during business hours, if not on a business day.
Questions d'entretien [1]
Question 1
How to build a summary table out of a written-in-a-notepad-document table of cricket wins and losses by country.
How to check the validity of an IP address string given some list of constraints.
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.
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.
4 rounds:
ML breadth + Depth: Conceptual knowledge about ML and work experience discussion
Problem solving: Leetcode (Medium) + Basic ML concepts
Design + LP round: Use case discussion + Behavioural questions
Bar Raiser - LP round: Behavioural questions - Interviewer was non technical
1
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