Internship: Pathway to hacking a career in Data Science

. 3 min read

I remember being told to score high grades and stay ahead of the curve to excel in the competitive world. High grades and good conduct was also a sure fire way to land a great job. But what I wasn’t told is that employers value hands-on experience more than qualifications. That’s where an internship comes handy.

Through an internship, a student or recent graduate to work, with or without pay, to gain experience over a limited tenure. The intern starts with a variety of responsibilities that help him gain a foothold. The high point of all this is that every single second of experience as an intern is several fold as valuable as the same second spent in class.

In an ever competitive and demanding workplace, an internship gives a candidate an edge over those who don’t intern. An intern has to work several processes which helps him develop insights into every single function. This hands-on learning is far more valuable than an academic transcript.

Data science is one such line of work where internships matter the most. Being an application based discipline, a budding data scientist needs to take up an internship with a data-focused firm. It’s here that he will learn how to apply what he learnt in class. This is validated learning – something that will increase his employability.

Reasons why an internship is a MUST for a Data Science career.

Real world experience

I touched above on the importance of hands-on learning in data science. Working for a firm, you can get controlled access to their data sets – data that is current and real. This will give you a realistic understanding of applying data science. You will also understand security and safety issues with handling big data. The analyses and conclusions you come up with will have some gravity and you will develop phenomenal accountability.

2. Resume builder

Internship = hands-on experience that matters the most to employers. This is not only helps you fill out space on your resume, it adds value to it. That means your resume gets bumped to the top.

3. Networking

Internships help you to build relationship with higher-ups in your field. As part of the internship, you attend meetings and seminars. These types of functions allow you to interact with staff and experts in the field. The professionals you work for may recommend you to other big companies as they have seen your performance.

4. Time management

As students, we are used to pushing our deadlines further but in an internship one has to stick to the deadlines. We learn to prioritize and manage our tasks. In addition, we learn to use digital tools to manage and track our tasks. This helps as using tracking and management tools is an imperative part of corporate work culture.

5. Intern to Full Time employed

Corporations used internships as effective screening tools to scout for future full time employees. If you work smartly and diligently, it might open up the door to full time employment.

Things to consider:

Bear the following things in mind while working on an internship in data science.

  • You have to complete at least one project all the way through to the end. This will help you understand how to solve issues, handle complex data, etc.
  • Practice manipulating large data sets in SQL, SAS, and other tools. As a trainee you should learn and practice how to apply your knowledge.
  • Learn to present your ideas or findings to the layman. This will help you reach out to all kinds of people and improve communication skills.
  • Build on your commitment and work ethic.

In a nutshell, internships provide you great exposure. Whether you are a student or a recent graduate, an internship is a sure shot way to develop yourself and improve you employability. One quick word of caution: internships are not a standalone virtue. Hence, interning with the right company matters.

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