4 challenges of recruiting data pros (and how to solve them)

If you’ve started trying to hire some too, you may have already encountered some challenges showing that recruiting is not as straightforward as expected. Here are four difficulties with hiring data experts — and how you can solve them.

1. Knowing and articulating the new hires’ roles in job ads

Data roles are in high demand. It’s due in part to the fact that companies have a growing collection of data from which they could extract value, but they don’t know how to get started.

In other cases, company leaders have paid attention to the increasing press coverage about data roles, such as how data science careers are among the most appealing. Then, they get the impression that they need to hire data professionals to keep up with other companies.

It’s true that bringing data professionals on board could make your company more competitive, but you need to have a clear reason for hiring them before jumping into the job market and seeing what it offers. Otherwise, the lack of specificity about why you want data professionals and what you’ll expect people to do will make well-qualified candidates steer clear.

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Some people also say that data science itself has become too vague and that people need to specialise more. For that to happen, companies must have defined plans in mind and fill their job ads with details that leave little doubt about whether candidates have what it takes.

It’s crucial that you don’t become overly eager and try to hire prematurely. Figure out how the data professionals will help your company first, then thoroughly clarify that need in job ads. Taking this approach should make recruitment easier.

2. Convincing your superiors to provide adequate hiring resources

Despite the leadership role you hold in your company, there are probably others in positions of authority above you whom you’ll need to address before you go into full-force hiring mode. If those people don’t give you enough resources to recruit properly, you’ll be at a severe disadvantage before getting started. Required resources include these individuals being willing to offer data professionals competitive salaries and other perks.

One of the realities that could present challenges is that data scientists are expensive to hire. Most job postings feature salaries of at least $100,000. Plus, data professionals overall are in such high demand that they know they can be choosy and prioritise the most appealing hiring packages.

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It’s essential for you to have in-depth conversations with anyone involved in giving you the resources necessary to hire. Discuss how the costs to recruit these professionals might seem high, but they’ll generate long-term successes for the company. You can also bring up how the benefits of getting hired might include alternative forms of compensation, such as an employee stock ownership plan (ESOP). That option benefits employers and employees alike and specifically lets workers have ownership stakes in the company that give them opportunities for wealth creation.

In short, if your company isn’t ready to offer an assortment of incentives that are on par with what other entities offer when they look for data professionals, you’ll have difficulty getting results.

3. Hiring when your company has an insufficient tech infrastructure

Data professionals will arguably be less likely to join your team if they realise your company’s infrastructure is so old that it doesn’t have the tools or capabilities that are critical for success.

According to a 2018 NACE report that looked at hiring challenges in recruiting for cyber security and data analytics roles, more than 38% of respondents said their companies did not currently have the data and tech infrastructure needed to derive value from information.

Interestingly, when their companies had outdated tech infrastructure, there was an even split of 44.4% responding “yes” and “no,” then 11.1% saying “I don’t know.” But then, when queried if their enterprises had updated infrastructures for data and technology, only 37.5% said they did.

With these statistics in mind, it’s smart to look more closely at your tech infrastructure and see if it could be a detriment to securing new hires. Job candidates will undoubtedly ask questions during the hiring process that help them determine your current readiness to focus on data. If the infrastructure is a significant shortcoming, data experts will likely look elsewhere for work.

4. Managing inaccurate perceptions about the candidates and how they fit with the company’s needs

When you’re hiring for any data-centric job, you have to make sure you have accurate perceptions about how someone’s background could benefit or potentially cause friction within your company. One data science expert weighed in to shed light on a persistent problem, mainly related to data science roles: companies believe they need to hire people who have PhDs to work in the field.

Then, if they find such individuals and hire them at for-profit companies to lead data science teams, those new workers end up frustrated and wanting to leave. There’s too much of a disconnect between academic life and the corporate world.

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You could encounter this pitfall in any scenario where what you perceive about the candidate — or what they perceive about what it would be like to work at your company — don’t align with the reality. Any recruitment process must focus on the advantages and disadvantages that each applicant offers, along with how those traits support or cause a mismatch with a company’s culture and what that entity requires of its data professionals.

Take the time to find the data professionals who seem best for the open positions, then dig deeper to make sure you don’t have the wrong ideas about what they’d offer. Make sure as well that they don’t have misconceptions about your company. Remember, data professionals are in demand. A persistent skills shortage means that if they aren’t happy at your company, they’ll leave and become associated with other businesses.

Obstacles that you can overcome

These four challenges should not discourage you from hiring data professionals.

Successfully recruiting them is not an impossible aim, but it’s important to understand and avoid situations that could make it unnecessarily difficult to attract talent.

Kayla Matthews

Kayla Matthews, is a tech journalist and writer.