The Ultimate Guide to Landing a Data Science Internship
As a beginner in tech, you’ve probably found it challenging to get the right data science internship. Questions about which firms to apply to and steps to take plague newcomers to the tech industry. Unfortunately, this worry isn’t out of place because internships can make or break your data science career.
Knowledge is power, so knowing a few strategic steps can land you your first data science internship in no time. Here, you’ll learn where to search for internships, requirements, and solid tips for getting a data science internship. Keep reading to discover more.
What Is a Data Science Internship?
A data science internship is any program where a beginner in data science can get hands-on experience, practice their skills, and clearly understand the scope of the field. It usually lasts around three to four months, but some may run for up to a year, depending on the organization.
As a data science intern, you’ll work with more seasoned professionals to fetch, analyze, and collate data and make professional reports on your findings. These activities eventually culminate in valuable industry experience relevant to employers, besides volunteer work or actual jobs.
Skills Required for a Data Science Internship
Before starting your search, there are a few skills you must have locked in place. Having these skills prior to sending out applications gives you a higher chance of landing a data science internship.
In addition, most companies will require that applicants have some background knowledge, and a few may give quizzes before admitting you. So we’ll see a few of them below.
1. Knowledge of Programming and Scripting Languages
Although programming isn’t a core part of data science, it can help you visualize and manage large, unstructured data. Python is the most commonly used data science programming language, but you may go further with R.
Other data science languages include Julia, Matlab, Java, SAS, and C++. However, remember, you’re applying as an intern; no one expects you to know everything from the start.
2. Knowledge of the Core Data Science Tools
Writing codes and learning algorithms will help automate some processes and arrange data, but that’s not the only necessary skill for a data science internship. You’ll also need to make charts, predict models, and properly analyze your data. This is where your data science tools come in.
Thanks to technology, data scientists now have options for collecting, collating, cleaning, and transforming data. One of these options isMicrosoft’s Power BI,a ground-breaking software that transforms bulk data into aesthetic charts and dashboards. For equally useful alternatives, go for Excel or Tableau.
3. Statistics
While it may look daunting, especially if you’re self-learning, statistics isn’t an unscalable hurdle. A background in statistics will enable you to relate to and analyze your data more effectively. Some key concepts in data science, like logistic regression and clustering, are built on statistics and mathematics.
A fundamental understanding of the subject boosts your chances of bagging data science internships and paints a clearer picture of your career path. Note that you canstart your data science career without a degreein statistics, so don’t let that worry you.
Tips for Getting Your Data Science Internship
What are the next steps to take to ensure you land choice internships? Learning many skills won’t do you much good if you’re not using them, so study these pointers below.
1. Work on Personal Projects
Practice, as they say, makes perfect, and this also applies to data science. To get selected for good data science internships, you need something to show in your resume or portfolio, creating the need for personal projects.
Many tutorial sites and courses have built-in projects or assignments that you can showcase. So rather than waiting till you’re at the finish line of your learning journey, build projects with any new knowledge you acquire. This way, you’ll have a variety of work to present when you’re ready to begin your search.
2. Create an ATS-Compliant Resume and Cover Letter
Once you have your projects ready, creating your resume follows. At first glance, this may appear easy, but seemingly minor mistakes could cost you later. One such mistake is failure to learnhow to write an ATS-friendly resume.
Although this isn’t strictly data science-related, it’s no less important. Making your resume ATS-compliant ensures that it stands out amongst several similar ones. Furthermore, you want to tailor your cover letter to suit the specific internship, rather than copying a random sample off the internet.
3. Build Your Network by Attending Data Science Events and Tech Workshops
Your network is your net worth, even in the tech world. Besides your applications, referrals and recommendations are another great way to land data science internships.
An extensive network skyrockets your prospects of getting that lucky recommendation, and attending events is a reliable method of building your network. There’s no rule against attending non-tech events, but you would benefit more from a network of people in your niche or related fields.
4. Reach Out to Startups
In the tech community, there’s a general misconception that startups don’t need data scientists. However, this is both false and limiting. Apply to more established firms, but don’t hesitate to inquire about available data science internships at smaller companies and startups around you.
5. Actively Utilize GitHub and Kaggle
GitHubandKaggleare like the equivalents of Facebook and Instagram for data scientists. With GitHub, you can store any codes you write and share them with hiring managers and interviewers.
On the other hand, Kaggle lets you write and share your Python and R codes, take courses on analysis, and win amazing prizes! Both sites have their pros and cons, so it’s up to you to choose which to use. Whichever you stick with, frequently push your codes and build an impressive presence.
Where to Find Data Science Internships
With your skills in the bag, a solid resume and portfolio, and a good network, you’re now eligible for data science internships. Here are a few sites to begin your hunt.
1.LinkedIn
Several firms and hiring managers post available internships and job opportunities on their LinkedIn pages. To take advantage of this, ensure you follow people in the data science or tech niche.
Also, like any social networking site, LinkedIn is a personal site that every professional can leverage. Tailoring your posts around data science and showcasing your learning progress can generate interest from companies looking to offer data science internships.
2.Handshake
This site is more targeted at college students, so if you’re an undergraduate, this one’s for you. Simply sign up, search for “data science internships,” and apply to any that pique your interest. The best part about Handshake is you don’t need previous experience, making it perfect for a beginner. Other popularwebsites for finding internshipsincludeIndeedandGlassdoor.
3. University Job Boards
If your institution has a job posting platform, then this could be beneficial in your search for data science internships. Also, studying a related course gives you a slight edge; feel free to contact and make inquiries from your professors and instructors.
Land Your Dream Data Science Internship With These Steps
By following the steps above, you can land the best data science internships that’ll grow your career in leaps and bounds. Proper training is the first step to a successful career, and there’s a world of them for beginners, depending on your preferences. Remember, they don’t have to be physical; virtual data science internships also count.
Gain some experience in the virtual workplace, and find a remote internship using one of these sites.
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