How to Land a Data Science Internship? The Ultimate Guide

Find out how to hand a perfect data science internship in this ultimate guide for beginners

You undoubtedly struggled to find the ideal data science internship as a beginner in tech. Newcomers to the IT business frequently have questions about which companies to apply to and what to do next. Regrettably, this concern is justified given that internships may make or break your career in data science.

Knowing a few clever moves will help you quickly secure your first data science internship in 2023 since knowledge is power. You may find information on prerequisites, where to look for internships, and helpful advice for landing an internship in the field of data science here. Learn more by continuing to read the guide to land a data science internship.

What is a Data Science Internship?

Any program that allows a novice in data science to gain practical experience, hone their abilities, and comprehend the breadth of the discipline is considered a data science internship. It typically lasts three to four months, although depending on the organization, some may last up to a year.

You will gather, examine, and compile data with more seasoned experts as a data science intern, and you will produce polished reports on your findings. In addition to volunteer work or paid employment, these activities eventually result in important industry experience useful to employers.

Skills Required

There are a few abilities you must have mastered before beginning your quest. You'll have a better chance of getting a data science internship if you possess these abilities before submitting your application. Moreover, the majority of employers will demand that candidates have some previous knowledge, and a select few could conduct tests before hiring them. Hence, a couple of them are shown below.

1. Knowledge of Programming and Scripting Languages

Although it's not essential to data science, programming may be useful for managing and visualizing enormous amounts of unstructured data. The most popular computer language for data science is Python, while R offers more flexibility. The languages Julia, Matlab, Java, SAS, and C++ are also used in data science. Nonetheless, keep in mind that you are applying as an intern; nobody wants you to be an expert right away.

2. Knowledge of the Core Data Science Tools

It will be possible to automate some processes and organize data by writing scripts and learning algorithms, but those are not the only skills required for a data science internship. Also, you'll need to correctly analyze your data, create charts, and use prediction models. Your data science tools will be useful in this situation. Data scientists now have alternatives for gathering, assembling, cleaning, and manipulating data thanks to technology. One of these choices is Microsoft's Power BI, a revolutionary program that converts massive amounts of data into appealing charts and dashboards. Excel or Tableau are good substitutes that are similarly effective.

3. Statistics

Although it could seem difficult, especially if you're self-taught, statistics isn't an insurmountable challenge. You will be able to relate to and evaluate your data more successfully if you have a foundation in statistics. Data science relies on statistics and mathematics to support some of its fundamental ideas, such as logistic regression and clustering. You have a better chance of landing data science internships and can see your career path more clearly if you have a basic grasp of the field. Don't be concerned if you don't have a degree in statistics since you can begin a career in data science.

Tips

What should you do next to guarantee that you secure desirable internships? If you aren't applying the talents you learn, then learning a lot of them won't be of much use to you.

1. Actively Pursue Personal Projects

As they say, practice makes perfect, and data science is no exception. To get picked for good data science internships, you need something to present in your resume or portfolio, generating the necessity for personal projects.

2. Create an ATS-Compliant Resume and Cover Letter

After your tasks are prepared, you may start writing your CV. This could seem simple at first, but seemingly insignificant errors could end up costing you. Failure to understand how to create an ATS-friendly resume is one such error.

3. Attend Data Science Events and Tech Workshops to Expand Your Network

Even in the IT industry, your network determines your net worth. In addition to applications, recommendations, and referrals are another excellent strategy to get data science internships. Having a large network increases your chances of receiving a favorable recommendation, and networking may be done effectively by going to events. Attending non-tech events is not forbidden, but networking with individuals in your industry or closely related professions will be more beneficial.

4. Make Contact with Startups

There is a widespread misunderstanding among techies that startups don't require data scientists. This is untrue and limiting, though. Apply to larger corporations, but don't be afraid to ask about possible data science internships at local startups and smaller businesses.

5. Use GitHub and Kaggle Often

For data scientists, GitHub and Kaggle are comparable to Facebook and Instagram. You can save any code you create on GitHub and show it to hiring managers and interviewees.