Just a few weeks ago, I had an interview for a data science internship with one of the largest telecommunications company in Asia.

I start next week.

How did I get the interview?

Hint: It wasn’t due to my education background (I haven’t even completed my CS degree yet). Neither was it through the data science certificates I once so diligently tried to collect.

I got called in for an interview because of my data science portfolio, and the projects I showcased there.

Applying for data science jobs can be pretty overwhelming, simply because it is nearly impossible to be a perfect fit for the company you are applying to.

My advice — Rather than trying to learn every tool there is out there, use what you know to build something useful. That is where you learn the most. Then, showcase your project to the rest of the world. Tell a story around it.

Creating projects you are passionate about does more than display your skill. It shows your love for what you do.

You will have to spend weeks (sometimes even months), trying to bring an idea to life. It is going to be hours of staring at your laptop, trying to fix your code that throws an error at you every time you try to run it.

Sometimes, you will realize that it** isn’t possible to finish your project** after spending a month on it.

There is no way to improve your model’s accuracy on actual user data because your data set is flawed.

That is a month’s worth of hard work down the drain, and you will have to start again.

Only a person who is truly passionate about what they’re doing can stick it through.

This will give an employer the confidence that you can get the job done. Even if you don’t completely fit the job description, you are someone who is capable of solving the task at hand.

#data-science #data-analysis #machine-learning #data #portfolio