How Can Undergraduates Prepare for a Career in Data Science?

Too Long; Didn't Read

I strongly believe that completing an internship is more valuable than a “ML related summer research project,” unless that research is done in the context of a respected laboratory at your university, and you have the explicit goal of publishing a paper that will help you gain admission to top graduate programs in machine learning. With that said, while internship roles in data science at tech companies are plentiful (see, for example, <a href="https://www.quora.com/What-companies-have-data-science-internships-for-undergraduates" target="_blank">What companies have data science internships for undergraduates?</a>), finding companies that actively hire undergraduates is non-trivial (in my experience). You’ll need to be aggressive, sometimes applying for and following up with recruiters on roles in which a graduate degree is “recommended” or even “required.” Finding companies that are willing to take a chance on a younger candidate will be an inevitable filter — luckily, several great companies are willing to engage with undergraduates. I evaded this artificial barrier by interning as a “data engineer,” and working on infrastructure related to the data science team. This gave me valuable insights into the day-to-day efforts of a data scientist.