An internship in data science can be a start to a very fruitful career. The demand for quality data scientist is on rise as more and more businesses begin harnessing the power of data in their decision making process. Before we get into the details let us start from the basics:

What is Data Science?

Modern Data science emerged in tech, with optimizing Google search ranking and LinkedIn recommendations to influencing headlines Buzzfeed editors run. But it is all set to influence and transform all sectors – whether it’s retail, telecommunication, agriculture, health or trucking. Yet many of us don’t really understand the meaning of ‘data science’ and ‘data scientist’

It’s true that data science is a wide field and depending on who you talk to you can get a different definition. They describe a wide range of work, including the massive online experimental frameworks for product development at expedia.com, the methods Buzzfeed uses to implement a multi-armed bandit solution for headline optimization, and the impact machine learning has on business decisions at Airbnb. Data science can be used in a number of different ways, depending not just on the industry but on the business and its goals.

Not to confuse you any further, here is the breakdown – First, data scientists lay a solid data foundation in order to perform robust analytics. Then they use online experiments, among other methods, to achieve sustainable growth. Finally, they build machine learning pipelines and personalized data products to better understand their business and customers and to make better decisions. In other words, data science is about infrastructure, testing, machine learning for decision making, and data products.

 What does a Data Science Intern do?

Most data science interns will be recruited by a company that have one or more senior data scientists. The inters responsibility can vary and you may get exposure of all or any one specific function of a data scientists’ responsibility. Ie. You may be responsible for helping the team set-up the infrastructure so they can capture all relevant data to run future experiments or you could be given responsibility to build an architecture to utilize data to answer a specific question the business has. Either ways most data science interns work with or under the guidance of senior data scientists – as each company has its own tools and methods. One thing is for sure regardless of your responsibility when you see a seamless architecture in place that solves problems by taking unstructured data as input is sure to get you excited and long for more.

How do I prepare for an internship in data science?

There are several steps that you can take to prepare yourself for the role – from taking online tutorials – free ones are good enough to grasp basic concepts and then there are programs like 21k Skills + Galavnize Data Science Bootcamps. However, here are a few steps recommended by Tawsif Hossain, a Computer Science & Machine Learning graduate from Northeastern University.

  1. Learn some Python.
  2. Familiarize yourself with the Linux environment.
  3. Learn SQL (the Structured Query Language) and how relational databases are structured. Popular DBs include MySQL/Postgres. Most of the world’s largest sites/apps use some kind of a database.
  4. Makes sure your stats background is rock solid.
  5. Play with some open-data, build some models and visualize some insights. Throw all of that onto a blog along with a nice write-up.

How do I prepare for a data science interview?

Remember that your basics need to be in place. We have many articles about nailing your interview and do’s and don’ts. So, for the purpose of this article, we will assume you have gone through them. Now, as mentioned earlier your role and responsibility as a data science intern will change depending on the sector you apply for but generally speaking companies look for individuals who are good in math and have some programming skills. The questions can vary from the field of statistics to machine learning to programming.

Ideally, we recommend having a talking point on your resume. That will surely limit the questions and tilt the scale in your favour. Write about a project where you used your skills and a platform like Github or something to solve a complex problem. You can find real world data set in the field of your interest and then work towards building and documenting the model.

Here is a great article by Kacper Kubara that we recommend for further reading.

Now that you are all set it’s time to apply for data science internships! At ECA we have helped over 7500 students get placed in 500+ companies. You can be our next! As you know, it all starts with capturing the right data – so fill the form below and we’ll connect you with a Data Science opportunity that is right for you.