Are you building to a bright cloud-based future?

We have noticed a trend towards companies seeking not just Data Scientists but Data Scientists with Cloud skills. Businesses are realising that they can save money and boost the scope of their data operation if they access data via the cloud rather than from big, expensive physical servers.

The power of holding data in the cloud is a very attractive one to the C-suite. What they need, in increasing frequency, are Data Scientists who are mathematically strong and also have the experience to deal with this data. And that is a problem.

We are constantly being asked the question: “What is a true Data Scientist?” As we should all know by now, the definition can range wildly from mathematicians, economists, tech heads to those within social sciences. This confusion can filter into job specs, creating a harder environment for actually hiring the required Data Scientist.

It is not unusual for companies to struggle when recruiting for their cloud data team. They seek out junior Data Scientists, and find them in abundance, because junior Data Scientists don’t need a lot of knowledge about cloud data to begin with. It is expected that they will learn as they go. They can join from university and there is no real expectation that they will carry the weight of a project on their shoulders. They are not expected to lead. Senior Data Scientists are needed, as they will have the experience that the juniors lack and they should have the authority to lead the business’ foray into cloud data.

The problem is that there aren’t really a lot of these qualified Data Scientists around. And the ones that are in existence, are in so much demand that there is next to no chance that they are not employed as we speak. The cream of the crop are those with multi-cloud environment experience and, of course, savvy managers are after these individuals above all else. But there is a problem.

When weeks turn into months and months, in extreme examples, turn into years, it is undeniable that something is going wrong in the hiring process. A closer inspection reveals that the problem may lie in the fact that the list of requirements for their perfect candidate to possess may be too extensive, including a few skills that, realistically, cannot be demanded of them. It is completely understandable that a company would want to cover as many bases as possible but it can turn into a problem.

The solution here is two-fold. It is about where you look and what you truly need from the prospect.

Most of the time, candidates the clients are looking for are not on the open market. They are in demand for a reason and simply posting job ads online will not cut it when it comes to finding them. If the recruiters are experienced and specialised, they know that the prospect needs to be pitched to or the prospect will simply not engage. The recruiter needs to know what your company actually does because, frankly, vague information does not work in enticing those prospects.

What companies must also understand is that even senior Data Scientists, or senior prospects in any field really, may sometimes need to train up in some disciplines, especially if the disciplines are new or expanding. A long list of requirements, and an unyielding attitude toward that list, mean your company will be waiting a very long time to fill that role. Knowing that fact comes with experience, so find someone experienced to guide you.

Curious about how Zenshin Talent can help your organisation? Contact us today for a no-strings conversation about your needs and our experience.