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Answer by Alex Francis, Data Scientist, on Quora:
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| Photo: Hemant Mishra/Mint via Getty Images |
How do I choose an internship that prepares me for a data science career as an undergraduate student?
I think the answer to this question really depends
on the company/role/industry combination, but if your background
resembles my own, I’ll take a stab at the question.
To start, I strongly believe that completing an
internship is more valuable than an “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, What companies have data science internships for undergraduates?),
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.
Secondly, I highly recommend choosing to work on a
product with which you have some familiarity. This is the most
underrated element of the decision-making process, in my opinion. As a
data scientist, you will constantly be called upon to generate and test
hypotheses about the product, produce insights, and suggest future
directions. If you’re an active user of the product, this isn’t nearly
as difficult — in fact, it’s often fun! Targeting companies that create
products you love will make you a better interviewer and a better
employee...
To summarize, successfully navigating a data science career is probably
not so different than managing a career in any other field: set some
goals, be aggressive, know your worth, figure out what’s fun and what
isn’t, reset those goals, and repeat the cycle.
Best of luck!
