Apple Data Science Intern Interview Questions

The late Steve Jobs followed through with his vision for Apple, making it one of the most well-known, innovative tech companies in the world. The launch of the first Apple iPhone in January 2007 forever changed the consumer tech landscape.

Apples economic footprint is massive. As of 2018, the company supported 450,000 US jobs and is projected to directly contribute $350 billion to the US economy by 2023. And even non-tech lovers want to land a job at Apple! Apple employs individuals in several disciplines, including technology, marketing, administrative, retail, operations, and accounting.

If youre part of the group that would love working at Apple, youre probably not surprised to learn that the companys interview process can be quite grueling; the company is known for asking a combination of challenging puzzle-based and behavioral interview questions.

The role of an Apple Data Scientist

Apple is a technology conglomerate that designs, manufactures, and sells consumer electronic goods, software/apps, and a variety of online services. Given the massive amounts of data its platforms such as Siri, iCloud and other online services constantly generate and handle, Apple needs data scientists who can help its platforms make sense of these huge data.

The role of a data scientist at Apple is different from those at other companies. It differs because Apple needs what is called full-stack data scientists. Apple expects its data scientists to be dynamic enough to work in different roles across its various teams such as the machine learning/AI-centric Siri team, analytics-heavy iTunes team, marketing, and sales teams, etc.

Skills required/preferred:

  • Practical experience with and theoretical understanding of various machine learning algorithms
  • Working knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and Spark
  • Mathematics, computing, and statistical skills
  • Coding skills in a general programming language such as Python, Scala, or Java
  • Ability to extract meaningful business insights from data and a knack for identifying patterns.
  • Excellent communication and presentation skills
  • The Apple interview process is similar to that of other major tech companies such as Facebook, Google, and Amazon. Candidates are required to submit their applications online. Those who make it to the interview round receive a call from the recruiter, usually an HR manager for the company. After that, candidates face a technical phone screen. Those who make it beyond this screening stage are called for an elaborate onsite interview. The location for the onsite interview may vary according to roles. It may either be in Cupertino, Austin or some other Apple campus.

    Required Skills

    Apple, for the most part, prefers to hire applicants with at least a few years of experience under their belt as a data scientist. The requirements are as follows:

  • 3+ years’ experience (5+ years for a senior position) applying data science to real business problems
  • Practical understanding of machine learning techniques such as regression, time series analysis, clustering, decision tree techniques, and experience with algorithms for classification.
  • Working knowledge of relational databases, including SQL, and large-scale distributed framework such as Spark and Hadoop.
  • Proficiency in numerical and scripting programming languages like SQL, Python, Java, C++, PHP, or Perl
  • Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways
  • Tell me about a time you completely failed. How did you bounce back from it?

    A behavioral question like this is a perfect example of when to apply the STAR method to respond. The interviewer will be listening for your level of honesty, integrity, resilience, and creativity.

    Early on in my career, I was selected as one of the three tech liaisons to work with HR for a confidential layoff that was occurring within the IT and finance divisions of the company. Part of the management team conducting the layoffs was overseas, which required confidential transmission of information and documents. This was before cloud-sharing, so our communication was primarily by email.

    We were up against a tight deadline to provide the proper severance communication documents, and I was responsible for submitting the documents to the team. I inadvertently sent the documentation to a name on the severance list instead of the hiring manager of that individual. Obviously, that was a huge fail considering the confidential nature of the communication, the fact that the individual was on the layoff list — it would be a huge blow for him to receive the communication ahead of time and by email.

    Fortunately, I immediately realized what I had done as soon as I hit the “send” button, and I contacted my manager and the HR lead for the severance program. We were able to work with our IT network lead to retrieve the communication before the individual opened the email.

    However, it was still a huge failure on my part, and I had to do the work to gain the trust of my team again. I took my time and practiced becoming more attentive from that point forward, and I did not make that mistake again. Eventually, I worked my way up and became a team lead for the IT department after a few years.

    The Apple Data Science Interview

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