How to Hire Data Scientists For Your Business?

Every business appreciates the importance of data and analytics. Even companies that have the most obsolete “data capture, store, and analyze” processes know they have to catch up or bow down. It’s not uncommon for today’s SMBs to budget generously for processes, programs, and technologies that bring them the power of data. Where’s the problem, then? For most companies, their lofty “data” programs end up merely creating pipelines to organize and accumulate data. To churn data, make data from disparate sources talk, and to build single versions of truth across business, you need the magic of a whole new kind of science. That’s data science, and these magicians are data scientists.

Here’s a little stat to put things in perspective. A recently published McKinsey report suggested that by the end of 2018, there would only be 200,000 available candidates for 490,000 open data scientist positions.

It’s clear — data scientists are hard to find, and consequently expensive to hire, and difficult to retain. On the other side, businesses must treat this as their lottery ticket, wherein they could simply get a leg up on their competition by hiring data scientists now and jumping a few months ahead. Next up, let’s tell you how you can hire data scientists.

Imagine. You decide to hire the best salesman in town. On Day 1, your instructions are clear — make us money. Will this work? No, 100 out of 100 times it won’t. Just like your decision to hire a salesman must be based on a conclusion that your product’s market potential and territory potential are underutilized.

Similarly, don’t expect a data scientist to walk in with a halo (or a magic wand). The decision to hire a data scientist must be made after establishing a case for the expensive hiring exercise. Ideally, your problems should be close enough to these, for you to look for a data scientist to solve them:

You get the idea, right?

Remember we mentioned how data scientists are hard to find? Well, that should give you an idea of how difficult this phase might be for you. It’s important to give yourself ample time rather than risk a hasty hire. Conventional channels of hiring aside, you will need to be as innovative and resourceful as you want your data scientists to be.