Apple Data Scientist Interview

Historical candidate account: this article preserves one person’s reported experience. The interview date was not recorded in the original text, and updating this page does not make the account a current hiring process. Names, levels, durations, questions, outcomes, and approximate compensation are as reported, not independently verified or endorsed by the employer. Confirm the current role and assessment with the recruiter.

Here is an Apple data scientist interview case study.

Apple Data Scientist interview summary

How it gets started: H.R. reached out on LinkedIn.

Job Level: Senior (IC4) 

Year of Experience: 8 years

Degree: Ph.D. in Mechanical Engineering

Offer: Yes

T.C.: ~300K USD

Location: Sunnyvale, CA

Interview process: 8 weeks

Team: Siri

Preparation: 2 months

Has a job: yes

Apple Data Scientist interview round 1: recruiter call

Team introduction, resume deep dive, relocation and other logistics discussion.

Apple Data Scientist interview round 2: data scientist peer technical round: Apple SQL Interview Questions 

Given a table of user login info, count the daily active users on each platform.

Apple Data Scientist interview round 3: hiring manager technical round

Team introduction, relevant experience, resume deep dive, how to cluster Siri users into different groups/segments, what algorithm to use and how to decide the number of clusters, how to evaluate the clusters.

Apple Data Scientist interview virtual onsite(4 rounds): 

1. TPM: basic product sense questions, how to improve iCloud.
2. Data scientist: favorite machine learning project, how to predict user utterance intention (for example, if a user ask tell me about apple, how do we know if it is regarding the fruit or the company).
3. Hiring manager: why apple? Are you more interested in business problems or technical problems? Some A/B testing and statistics questions.
4. Director: what do you think you can bring to apple? What is your most proud project? Any questions for me?

Apple Data Scientist offer

Received the offer two weeks after the virtual onsite interview.

Prepare a metric and a modeling explanation

For daily active users, define an eligible activity, a reporting timezone, and one distinct user per platform per day. A user active on two platforms belongs to both platform counts, so their sum need not equal total distinct users. For clustering, explain the purpose, feature scaling, stability, and how the groups would be used; a numerical cluster score alone does not establish usefulness. For an ambiguous utterance such as “apple,” discuss permitted conversational context, label quality, uncertainty, and a fallback when the intent cannot be resolved reliably.

Practice one reported prompt, state the data and assumptions, produce a checkable answer, and explain one limitation. Then change a condition and see whether your reasoning still holds. Use this related practice resource for a follow-up; it is separate from the historical interview report.