Solicité el puesto a través de un captador. Acudí a una entrevista en Apple (Cupertino, CA) en abr 2019
Entrevista
I went through 3 phone interviews before I was invited for an on-site interview. The first interview was a 30 minute phone call with the hiring manager. He asked about my past experience and basic data science questions. The next call was with a data scientist on the team who asked me to code in python. The third call was with a senior data scientist that asked basic machine learning questions. The on-site interview was a whole day ordeal. I got there at 10:30 am and left at 4:30 pm. There were several 30-minute meetings with data scientists, machine learning engineers, managers, etc.
Preguntas de entrevista [1]
Pregunta 1
What is Variance and Bias?
How do you decide whether one classification algorithm is better than the other?
What is a naive bayes classifier?
Describe neural network
Draw a confusion matrix and calculate precision and recall
Coding questions included binary tree implementation and computing ngrams in python.
Envié una solicitud electrónica. Acudí a una entrevista en Apple
Entrevista
First Round: 2 questions on SQL (hard) and Scenario based question was given. You have to provide a detailed answer on what kind of framework you would build on the scenario.
The interview process for the Data Scientist role at Apple consisted of three rounds
First round: screen with a recruiter
Second round: screen with a hiring manager
Third round: a virtual on-site with 3 interviews
The interview process consisted of multiple rounds, including an initial recruiter conversation followed by several virtual interviews with team members. The interviews focused on my background, past data science projects, machine learning fundamentals, statistical thinking, and how I approach business problems with data. There was also discussion around cross-functional collaboration, communication, and how I would translate technical insights into actionable recommendations. Overall, the process was rigorous and comprehensive, with a strong emphasis on both technical depth and practical problem solving.
Preguntas de entrevista [1]
Pregunta 1
Tell me about one of your data science projects and explain the business problem, your modeling approach, the metrics you used, and how you communicated the results to stakeholders.