Data fuels the digital transformation process. At least, it should. That’s why you see more and more companies talking about positions like “data scientist,” “data engineer,” and “data translator.” They realize that without this key position, they’ll never be able to assemble a solid digital transformation plan. But what do data scientist skills look like? Outside of, “Must be good with algorithms,” what do we look for in a successful data scientist hire?
It might be an unpopular view, but I think the data science team is going to outweigh the CEO in terms of overall value-brought-to-enterprise in the coming years. That’s because when you assemble the right data science team, you’re moving and shaking. You’re thinking outside the box, and far beyond it. You have the power to do things like understanding your customers and competitors and even future customers all in real-time—something a single human could never do. Defining the right data scientist skills now is essential to your overall digital transformation goals.
Data Scientist Skills: They Might Surprise You
Just like IT is getting a general overhaul in digital transformation, so is the type of person the enterprise needs to hire to fill new IT positions. The data scientist position is no exception. While it’s easy to think of algorithms and assume a data scientist is just a “numbers” person, a true data “hero” is so much more than this. Because the role they play is so essential to success in digital transformation, they need to be equal parts analyst, dreamer, and communicator. Maybe that’s why so many companies are having such a hard time finding the “right” one.
Regardless, which type of data scientist you’re looking for, the following are my top three qualities to hire for.
Analyst. Of course, it goes without saying that the data scientist—no matter what field they’re working in—needs to have an analytical mind. They need to be able to think in logical terms, to find patterns—even far reaching or deeply buried patterns—and they need to be strategic enough to use that information to improve the situation at hand. For instance, if we notice that your sales dip at a certain time in a certain part of the country every Tuesday night like clockwork, they need to know what information will get to the why. Data that doesn’t answer a why is merely information. And information is not nearly as valuable in digital transformation.
Dreamer. In addition to being analytical, your data scientist also needs to be a dreamer. Yes, data scientist skills lie on opposite ends of the spectrum. But you need to find someone who lives and eats data. Someone who is constantly asking questions … and passionate about finding the answers. Not only that, you need to find someone who is constantly finding new questions to ask and new directions to go. People who can develop their own hypotheses and test them quickly. This is the only way not to become stagnant in digital transformation.
Communicator. For now, one of the most important data scientist skills is also that of “communicator.” Why? Because right now, many companies are between old and new. They have leadership skills who kind of trust data—but still trust their guts more. They have old-school siloes that need to be bridged. They have people from different silos—with different degrees of technical competence—asking questions that they need to answer in clear and trustworthy ways. I say “for now” because Gen Z is in college. Pretty soon we won’t all be operating in that tech gap of legacy mindsets and digital transformation. Yes, they’ll still need to be able to share an idea or push an idea forward. But they won’t have to push quite as hard to get it out of the gate, in my opinion.
And lastly, you need someone who knows the ins and outs of your company. Does that mean you need to hire someone from within? Not always. It means you need to know your company well enough that whoever you train on culture, mission, purpose, and business goals will get it. They will understand what you’re trying to achieve and can hit the ground running giving it to you. Strategy, culture and clarity still play a huge role in digital transformation. Even if they aren’t technically part of data scientist skills to hire for, they are still things you need to get shored up before hiring the right employee if you want that data employee to be successful.
McKinsey guesstimates we’ll need up to 4 million data translators by 2026. Obviously, quality will vary widely in a pool that size. As with anything in digital transformation—the specific skills, software, apps, etc. that go along with hiring a good data scientist are far less important than the qualities they carry within them. Strong Analyst-Dreamer-Communicators need only apply.