J'ai postulé via un recruteur. Le processus a pris 2 mois. J'ai passé un entretien chez Apple en déc. 2021
Entretien
Quite an interesting experience. The recruiter reached out in Aug and I replied back with time for initial screening. She then disappeared for 2 months, later on responded back saying that my email slipped through the crack. I was still in the market so we talked. Then she passed my information over and one HM picked up my resume. We then had a 45-min tech screening which ran over to 1 hour. HM was passionate, asked 2 coding questions and some behavioral ones. The final interview was a day-long loop, starting from 9 am and running all the way till 5 pm (7 interviews in total). I met with multiple people and stakeholders of the team. Heard back from the recruiter with positive feedback in a week. Despite the initial ghosting, I would say the whole recruiting experience was pleasant and efficient.
Questions d'entretien [1]
Question 1
Walked me through a project that you're most proud of.
Some metric design questions
Mainly case studies around various Apple app lines
J'ai postulé en ligne. J'ai passé un entretien chez Apple
Entretien
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.
J'ai passé un entretien chez Apple (Culver City, CA)
Entretien
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.
Questions d'entretien [1]
Question 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.