Apple’s dominance in domains such as development, design, consumer electronics, online services, and computer software is in a league of its own. The tech giant is extensively looking to hire passionate, creative, and dedicated data science professionals in their organization.
From their AI development team at Siri to the cloud-base architecture team at iCloud, Apple has been able to steadily move toward building a data science team, thus, they’re in the constant lookout to hire data scientistswho can easily handle data.
Are you a data science enthusiast or just one of those people drawn to become a part of Apple?
Working for a tech giant like Apple offers the same benefits provided by many other tech companies like Facebook, Amazon, and Google, etc. lucrative salary, the swag, free food, free gym, and amongst all the prestige you get to carry among others.
As an organization, Apple is hierarchically aligned as a functional company and is surrounded by multiple levels of verticals and expertise. As mentioned, the company gradually started building its Data Science Interview Questions team and now needs to hire an efficient data scientist professional.
Before moving further, let us first discuss the highlights of a data scientist role at Apple
The job role and responsibilities entitled to a data scientist vary differently and are dependent on the specific team you’ll be assigned to work with. However, the actual job title of a data scientist is the closest thing to a job title called ‘a full-stack data scientist.’ As such that the job role requires the individual to take up tasks from machine learning software design to analytics and plain engineering.
Since Apple is considered to be a huge multi-conglomerate. Moreover, the data science skills used can vary according to the team – finance, marketing, sales, machine learning, and deep learning teams having close interaction with products like Siri and cloud services.
The interview process
Like any other company, even Apple has a standard way of conducting their interviews. It has the same phone screen interviews followed with a couple of four to five more interview rounds.
The first round happens like the usual standard round. The HR gets to the candidates, finishes off with the preliminary screening, then the hiring manager checks whether the profile fits the designated role assigned by the company along with technical rounds of course. Once all these rounds are over, at times the candidate has a take-home assignment based on the seniority of the job role before heading to the onsite interview.
The take-home assignment
The technical screening round is done in a shared coding environment. Most of the questions given to the individual include data science reasoning questions and general Python exercises. Earning a data science career at Apple does only needthe courage but the required skill set to get past the interview. The candidate must communicate their thought process during the technical screening. At this point, your ability is being analyzed and your knowledge about how best you can use data structures and whether your concepts about algorithms are clear.
The take-home assignment is often given under a certain limit, such as one to three days. The take-home assignment generally composes of solving a machine learning problem or how to build a model or perhaps how to make a prediction of a dataset.
The on-site interview
Onsite interviews are the last round of interview the candidate must undergo. The final round of the interview consists of a group of panel members. These members are usually the oneslooking to hire for their team. For each interview, the candidate will have two interviewers taking their interviews along with lunch arranged at the Apple campus itself along with the hiring manager.
Although the hiring setup might not be a formal procedure, it checks out the cultural fit of the candidate looking to be hired.
A data scientist professional at Apple is highly paid owing to the level they get hired.
If you’re hired at Apple, you should know you’re at one of the most challenging workplaces to work in the world.
What’s even best, you’re surrounded and fully loaded with the best in the industry.
Companies like Google, Facebook, Amazon, Microsoft, and Apple rank as the best places to work.