computer screen with lines of code

Data Science Internships: What are They and How Can You Get One?

Suppose you’re interested in embarking on a career spent harnessing the power of machine learning to develop exciting new methods and techniques of data analytics. In that case, you might be considering entry-level data science positions. And who could blame you: with the US data science job market expected to grow by 36% over the next decade, over 7x the anticipated growth rate of the US job market as a whole, and salaries averaging around $82,000, well above the US median annual wage in the US of $45,760, an entry-level data science position is a perfect first step to a rewarding career.

But suppose you’ve already researched these positions. In that case, you’ve probably encountered an age-old dilemma: recruiters and hiring managers for these entry-level positions are interested in candidates who can demonstrate work experience, sometimes even 1 to 2 years. Often, a capstone project, college degree, or bootcamp certificate isn’t enough to extract yourself from this Kafkaesque chicken-and-egg scenario. 

Thankfully, there is something that can: a data science internship. Below, we’ll dive into everything you need about these exciting opportunities that can take you one step closer to your first data science gig

What’s a data science internship?

Data science internships are geared towards individuals in the process of an educational program in data science or a related discipline or who’ve recently completed an educational program. While some companies hire students as interns who are amid a data science bootcamp or bachelor’s degree data science program, others want their internships to be current data science master’s or Ph.D. candidates. While summer internships are common, year- or semester-long internships are also available.

You’re immersed in a company’s day-to-day as a data science intern. Working on one or several teams during your internship, you’ll complete tasks matched to your current skill level and receive mentorship to help you level up. Potential tasks include dashboard creation and maintenance, debugging, documentation writing, data pipeline creation, and analytics.

While in other industries, many internships are unpaid — a controversial business practice, to say the least — the good news is that most data science interns receive monetary compensation in addition to college credit and the other non-pecuniary benefits they offer. Some interns, especially those at big tech companies, are paid quite handsomely: at Amazon, for example, a summer intern can expect to earn around $55.38 per hour. Often, internships at these kinds of companies can turn into permanent positions. Understandably, competition for these opportunities is fierce, with some even seeing thousands of qualified applicants. 

What skills do you cultivate in a data science internship?

Each data science internship is different in terms of the skills it requires applicants to have at the time of application and the skills it provides the opportunity to develop. As a general rule, the skills cultivated in a data science internship include skills in:

  • Computer science: programming languages like SQL, Python, and R; software engineering; data management, including big data management

  • Applied mathematics: statistical analysis; probability; linear algebra

  • Machine learning: machine learning model design; techniques like regression and decision trees; advanced areas like natural language processing and deep learning; tools like Pandas and other machine learning libraries

  • Data visualization: dashboards and other visualizations using tools like Tableau

  • Industry-specific knowledge and techniques

What career paths can a data science internship prepare you for?

A data science internship will best serve the aspiring data scientist, but it can also prepare you for several other careers, including:

You can find more on these positions in our articles on data science, data analytics, and business analytics careers.

What are some examples of data science internships?

We’ve covered what a data science internship is, the skills you can learn, and the careers you can prepare for. Now, let’s get a taste of the kinds of opportunities out there.

ibm logo

IBM: Data Scientist Intern, Summer

Data scientist interns at IBM gain exposure to commonly used machine learning techniques and IBM’s proprietary set of analytics and machine learning tools as they oversee the lifecycle of data science models from implementation through maintenance. IBM requires candidates to have existing experience in programming and technical maintenance, as well as some degree of exposure to design thinking and Agile development.

reddit logo

Reddit: Data Science Intern

In hiring data science interns, Reddit looks for students currently pursuing master’s or Ph.D. degrees in data science, computer science, or a related field who are proficient at SQL and have less than two years work experience. Ideal candidates also know how to program in Python and have experience both in the social media industry and with quantitative social science research. As a data science intern at Reddit, either in San Francisco or New York City, you have the opportunity to work on a variety of projects related to content moderation, fraud detection, and user experience while being mentored by data scientists at all stages of their careers.

uber logo

UberSTAR Internship Program - Data Science

For Uber’s 2023 UberSTAR internship program, they seek freshmen and rising sophomores majoring in statistics, computer science, or a related field who have experience coding with SQL, Excel, dashboards, and data science basics such as statistical modeling and experimental design. During the program, interns work under the supervision of an analyst with other data scientists and engineers on a variety of projects, with tasks including data analysis and insight presentation, dashboard design and development, and data pipeline management.

moodys logo

Moody’s: Data Science Intern

For this summer intern focused on an ESG-related initiative, Moody’s seeks a master’s or Ph.D. student with experience in machine learning and programming fluency in Python or R. The intern’s primary responsibilities will include writing documentation, improving dashboards, assisting implementation efforts, and ensuring machine learning algorithm compatibility with Moody’s ESGC score predictor.

How do you land a data science internship?

These are just a couple of examples of the data science internships out there, and they may not be a good fit for your interests or profile. So, how do you find a data science internship that will work for you, and, more importantly, how do you land one? 

You can easily find data science internship opportunities through job posting aggregators like LinkedIn and Indeed and on the careers pages of companies you are interested in. When it comes to getting an offer, you first want to make sure that you identify internships that interest you early — recruitment cycles begin well before an internship’s start date — and apply to several opportunities to maximize your chances of getting a spot.

While application requirements vary, employers generally want intern applicants to provide a resume, cover letter describing their fit for the position, and occasionally unofficial or official transcripts attesting to degree status. Some will also request a portfolio of data science projects to date.

Contact your university’s or boot camp’s career services office or your academic department to express your interest in an internship is also a good idea. Many of these cultivate relationships with employers that can help your application get preferred status. Reaching out to your personal or professional network can also help increase the chance that your application gets noticed.

Finally, you want to appear polished if and when you get an interview. Completing some internet research and even informational interviews with alumni of the internship programs you’re interested in can help you get a better understanding of what the employer is looking for, what they’ll ask you in your interview, and whether you’ll be required to complete any take-home projects as part of the process.

When it comes time to apply, check out our resources on crafting the perfect data science resume and cover letter.

What comes next? 

After you’ve completed one (or several!) internships, you stand a better chance of getting an entry-level data science position. When the time comes, head to our step-by-step guide to getting your first data science job for helpful advice. For more on what an entry-level position entails and the opportunities it can bring, see our breakdown of the typical data science career path.