Data can yield uncomfortable truths, sometimes about data science itself.
In 2022, almost 50% of developer-focused recruiters testified to having difficulty finding qualified candidates. Though our world is increasingly data-dominated and data-powered, there is a growing data science skills gap that will take years to fill.
With talent thin and competition for candidates fiercer than ever, how can organizations find the team members they need?
To grow our team at Heap, we refined our processes when traditional strategies failed to help us fill data science roles. Data specialists, and those with other in-demand skills, hold power in today’s employment market. As a result, the most accomplished and prominent specialists can expect frequent recruiter calls and weekly poaching attempts. That’s why any company seeking to attract and retain talent needs to know where to look and how to make a strong first impression with a prospective candidate.
[ Also read IT hiring: Tackling the cybersecurity skills shortage. ]
We identified three key challenges emerging technology companies face due to the talent shortage. The strategies we’ve developed to address them have brought us hiring success in competitive situations, even against larger vendors.
1. Conventional job boards fail to produce candidates
Hiring managers searching for talent may be looking in the wrong places. For example, AngelList deserves its high reputation in the tech world, and we post our traditional roles there. But we learned that LinkedIn, a tried-and-true avenue, yields better and swifter results when hunting for more unusual skills.
Similarly, we’ve learned to lean on our established thought leaders. While the relatively small size of the data science community poses challenges to businesses looking to hire, data people are a genuine community, and actively participating in that community can be a powerful tool.
A hiring tip: When your engineers contribute to open source projects, be sure to highlight that work in relevant communities.
[ Career tips for open source: 7 strategies for success when contributing to open source ]
2. Traditional job descriptions aren’t attracting the right talent
Data scientists and engineers tend to be inquisitive. They’re not interested in rote tasks; they want to identify problems, interpret unique datasets, write precise code, and devise elegant solutions. For that reason, job postings and interviews should emphasize the actual issues data scientists work on and clearly state the challenges involved to attract and engage potential hires.
This clarity helps both candidates and recruiters: Candidates get excited about contributing and hiring managers gain an early sense of how the candidate will approach the job.
One piece of advice for candidates: A shocking percentage of job seekers lack clear résumés or send vague CVs. It’s the details that make a résumé pop. A line on your CV announcing that you “performed statistical analysis” is not especially helpful. Hiring teams notice specific descriptions such as “performed statistical analysis using <specific tool> to pull insights from X data sets.”
[ IT careers: How to get a job as a data scientist ]
3. Your candidates aren’t qualified
There are countless directions that a data scientist can move in; no two people have identical skills. Acknowledge differences, admit areas for improvement, and focus on candidates’ strengths.
For example, a product team should consider candidates even if they lack a product background. You can often find very successful and innovative employees with unusual or unexpected backgrounds.
Successful hiring in challenging times
In today’s employment market, specialist candidates hold power. Any company seeking to attract and retain top talent needs to know where to look, how to make a solid first impression, and how to balance gaining a candidate with specific skills with requirements that could limit your candidate pool.
By establishing responsibilities, contributing to technology communities, and accommodating individuals’ unique skill sets, hiring organizations can set the stage for long and productive tenures from highly skilled contributors.
[ Leading CIOs are reimagining the nature of work while strengthening organizational resilience. Learn 4 key digital transformation leadership priorities in a new report from Harvard Business Review Analytic Services. ]
