About the role#
The Applied Data Solutions Program is a summer internship focused on applying your technical background to real-world problems. You will work within the Corporate Functions team to develop data-driven solutions while building your professional and technical skills. This is a full-time, 40-hour per week program based on-site in Austin.
What you'll do#
- Solve real-world problems using data-driven solutions.
- Work directly with Apple's data infrastructure and analytics platforms.
- Engage with data challenges to develop your technical expertise.
- Collaborate with your team to deliver measurable impact.
- Receive mentorship to support your growth.
What you'll need#
- You are a current student pursuing a degree in Computer Science, Data Science, Computer Engineering, Statistics, or Mathematics.
- A strong interest in data, analytics, and solving complex problems.
- Curiosity and the ability to work well in a collaborative team environment.
Location & details#
- Location: Austin, Texas.
- Term: Summer 2027.
- Modality: On-site.
- This position is a paid internship.
About Apple
Apple designs and manufactures consumer electronics, software, and online services. Founded in 1976, the company maintains its headquarters in Cupertino, California. It operates in the computers and electronics manufacturing industry. The organization employs over 200,000 people globally.
How to get in at Apple
Securing an internship at Apple requires speed, as early applicants are often reviewed before the volume of candidates becomes unmanageable. Intern Insider sends an instant alert the moment a role matching your target is published, helping you apply among the first. This timing often provides a distinct advantage in the initial screening process. You can also improve your response rates by reaching out to recruiters directly to ask about the role or a referral. Intern Insider surfaces the specific recruiters behind Apple roles, allowing you to bypass the standard queue and connect with the people actually making the hiring decisions.
