Dear Aspiring Data Scientists: Skip the Certificates, Do This Instead

If you've been on LinkedIn anytime in the past several months, you've probably come across the infamous "certification post."

Users show off their certificates or "statement of participation" in almost anything, from LinkedIn Learning courses to attending webinars or completing a coding quiz.

I'll admit, I'm guilty of this as well, and I'll explain why below.

Certificate posts have several powerful drivers:

First off, one post can easily garner tens of thousands of views, and this validation sparks a primal "fear of missing out" in viewers. What if everyone has a certificate except for me? And so, the next person gets a certificate just to share it on social media and feel like they're part of the crowd.

Secondly, most social media algorithms include a "positive spiral" of engagement. Feed optimization algorithms include inputs like "number of likes" and "number of comments," so that popular posts get moved to the top, such that the psychological FOMO of certificate posts is algorithmically fueled as well.

Finally, social media sites like LinkedIn want growth and engagement at any cost. Without non-stop growth, social media platforms join the endless graveyard of failed experiments.

As I've shown, certificate posts simply "work," in terms of getting engagement. This is part of why LinkedIn acquired Lynda for a whopping one-and-a-half billion dollars.

LinkedIn Learning certificates now fuel massive engagement, with a major caveat: This engagement isn't by decision-makers, but rather by other students.

What this means is that, while you're likely to get thousands of views, you won't actually get the attention (and more importantly, admiration) of those in a position to hire you.

For every "certificate post," there's another post complaining about certificate posts. Lest this article succumb to the same irony, I'll present an alternative.

If we look at data science career trends in 2020, we'll see that there's still massive growth in global advanced analytics employment.

In other words, there's a lot of opportunity for those with the skills, not those with the certificates.

This growth isn't over, as there are still tens of thousands of unfilled data science roles.

To be one of the lucky few who lands such a role, you need to share content that shows you're both passionate and skilled, which certificates typically fail to do.

First, pick a topic you're interested in. Then, analyze the associated data, creating insightful visuals and commentary (basically, do data science). Finally, share these insights.

We all know that shared articles don't get read by most viewers (except for the headline), so sharing a dashboard instead is a fantastic way to show your passion and skill in a format that attracts attention.

For inspiration, you can look to the data science career trends dashboard mentioned above, and other analyses like diversity in big tech or coronavirus search trends.