How to Land a Data Science Internship: Your 2026 Guide

Key takeaways

• To get a data science internship, submit your application well before the deadline, apply to multiple opportunities, create a portfolio, and refine your resume and cover letter.

• Data science internship jobs allow you to gain professional experience, practice technical skills in a real-world setting, and enhance your resume as you begin your career.

• You can build relevant skills to prepare for a data science internship by learning about programming and scripting languages and enrolling in an undergraduate or graduate computer science program.

Explore various data science internship opportunities in data analysis, machine learning, computer vision, data security, and more. Discover more about data science internships, including where to find them, how to apply, and what skills to develop. If you’re ready to build career-ready skills for an internship, consider enrolling in the University of Michigan’s Python for Everybody Specialization. In as little as two months, you’ll have the opportunity to learn about fundamental programming concepts, such as data structures, networked application programming interfaces, and databases. 

Data science internship: Benefits, duties, and required skills

A data science internship can be the first step to starting a career as a professional. Offering hands-on experience in the work world, internships can provide networking opportunities, give you the chance to work with complex data sets, collaborate in a team environment, and experience the direct impact of your field of study. 

Each data science internship will have unique benefits, duties, and skills required for the position. While every internship is different, the following sections outline what you can expect from most data science internships. 

Benefits

Internships offer many potential benefits, including the opportunity to gain work experience, practice your technical skills in the real world, and build your resume to help you on your career path. 

Typically lasting for a fixed amount of time, such as four months, internships also allow students and early career professionals an opportunity to connect with a network of industry professionals. In some cases, an internship might even lead directly to a job later.

Skills

As a data science intern, the skills you’ll use may vary from one position to another. If you are a graduate student, you'll likely be expected to perform many more duties than an undergraduate in a similar position. 

The list below includes some of the common skills expected of data scientists, which you will likely encounter as an intern in the field. 

Technical skills

Data scientists have a well-honed technical skill set that allows them to gather, analyze, and visualize data while developing data models that guide decisions and predict outcomes. 

To perform all these critical duties, data scientists must often have a firm grasp of the following technical skills: 

• An understanding of programming languages, such as SQL, Python, or R

• The ability to visualize data by using such data science tools as Tableau and Power BI

• An understanding of how to use machine learning to collect data and develop predictive machine learning models

• A grasp of software frameworks, such as Apache Hadoop, for processing big data

People skills

Data scientists must work with both experts and non-experts to ensure that the best data is collected and the best decisions are made. As a result, you must embody some of the following common people skills: 

• Teamwork

• Communication 

• Problem-solving 

• Storytelling 

Data science internships: Where to find them, entry requirements, and tips on applying

The first step to landing a data science internship is finding one. In this section, you'll learn where you should look, some common requirements, and tips to help you when you apply. 

How to find a data science internship

You can find a data science internship by searching for available internships on a job posting website or by searching for internships on a business’s dedicated job page. 

Job posting sites

To find a data science internship on a job posting site, go to your site of choice and search for “data science internship.” From there, you can view a list of currently available internships.

Some popular websites to search for internships include: 

• Handshake

• LinkedIn

• Indeed

• Vault

Business’s dedicated job page

To find an internship on a business’s dedicated job page, go to a search engine, such as Google, and search “[business’s name] jobs.” Once on the dedicated job page, search for “data science internship” and see if any are available. You might also consider searching for a related position, such as “data analytics internship” or “data science engineer internship.” 

How to prepare for a data science internship: Requirements

The requirements for each data science internship will depend on the nature of the position. Nonetheless, some of the common internship requirements include: 

• A grasp of programming languages, such as Python, Java, or C++ 

• An understanding of scripting languages, such as SQL, Python, and R

• An ability to work with others in a fast-paced environment

• Research experience

• Enrollment in an undergraduate or graduate degree program in computer science, mathematics, statistics, or a related field

Keep searching

While many data science internships are geared toward those already enrolled in a relevant master’s degree program, some target undergraduates or even high schoolers. No matter your current education level, internships are likely available to you.

How to get a data science internship: Tips on applying

When applying for your internship, put your best foot forward. To help improve your chances of landing your next internship, consider the tips below. 

1. Apply in advance: Internships can be competitive, so it’s helpful to make a good first impression by applying well in advance of the deadline. For example, if you're applying for a summer internship, apply much earlier in the year or, in some cases, in the fall of the previous year. Being early will also give you time to ensure all your application materials are complete. 

2. Apply to more than one internship: Data science internships can attract many strong applicants, so it’s best to apply to many internships rather than pinning your hopes on just one. 

3. Create a portfolio: A portfolio of your past or current work can highlight your skills in action and be a good supplement to your application. 

4. Lean into your network: Your existing network of professional contacts could be a helpful resource for identifying available internships and soliciting feedback on your application material. 

Read more: 9 Networking Tips to Expand and Strengthen Your Network

5. Get a recommendation letter ready: Your application will likely require a letter of recommendation from a teacher or relevant individual who knows you well. Writing a recommendation letter can take some time, so ask your recommender at least three weeks before the deadline. 

6. Fine-tune your resume and cover letter: Tailor your cover letter and resume to each internship. Your cover letter and resume represent you professionally, so make sure to proofread both before submitting them. 

Types of data science internships

As you search for data science internships, consider specializing in an area related to your interests and future career goals to get the most value from your experience. You can also use an internship to help you decide which career path to take. Some types of data science internships include:

• Data analyst intern

• Machine learning engineer intern

• Data scientist intern

• Business intelligence intern

• Data engineering intern

• Natural language processing (NLP) intern

• Computer vision intern

• Data security intern

• Health care data science intern

• Marketing analytics intern

Prepare for a data science career with our free resources 

Visit our Career Resource Hub to assess your skills and explore career tracks. Then, check out these free resources to learn more about data science: 

• Expand your learning: Data Science Learning Roadmap: Beginner to Expert 

• Learn your terms: Data Science Terminology and Definitions 

• Read our Career Chat issue: 5 Data Science Certificates to Bolster Your Career

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