The advanced analytics space is all about results. Your company expects the data team you built to deliver actionable insights that improve the company. However, when that same team fails to achieve the desired results, you get the brunt of the blame.
The market for data science talent is tight, and it doesn’t give you much range to find top talent. Sometimes it seems like finding qualified analytics professionals is like looking for a needle in a haystack. Even when you think you have hired the right person, you are left scratching your head when that person turns out to be a bad hire. You ask yourself, “what am I missing? What do I need to change?”
Here are some things to think about during your next data talent recruitment.
You already work with the hiring manager to craft a good job posting, and you rely on an ATS to screen out the wrong candidates. However, this process is not getting the results you and your company desire. Here are some things you could do to improve your process and increase the range of applicants.
Because of the dynamic nature of the data science industry, the range of specialized skills within this field, and the evolving nature of deliverables expected from the your analytics/data team, the usual process just won’t work. Try shadowing employees, and also meet with the corporate training department for any insights they have to trends they are seeing.
Strong quantitative and programming skills are non-negotiable. You should screen for and assess these skills first; that means before a candidate sits down with a hiring manager, understand their skill set. Assessing first will narrow the range of capabilities so you can focus on the candidates that best fit your need.
Another advantage of pre-assessing candidates is that you will find out if the candidate has the needed skills before you find out whether they fit culturally. Looking for culture fit first increases the chances that the candidate will not get results and leave prematurely by your choice, if not theirs.
Traditionally, you use the ATS to filter people who don’t match the job requirements. With the tight labor market, scarcity of trained data specialists and amount of transferable skills, the ATS could be eliminating good candidates. A one-to-one match for particular software may not be a requirement, where experience with certain elements of data science work may be. By focusing first on the ability and experience in the particular area of data science before running candidates through the ATS filters could improve your talent pool.
Working with a analytics talent partner can help you improve your recruiting process. This partner can test the skills of potential candidates for you related to the work your current data team does. By testing candidates before they sit down with your hiring manager, you will be confident that they have the desired skills. This process will give you a wide range of qualified and vetted job applicants.
It is unlikely you could do away with your ATS or the subjective aspect of the hiring process altogether, like looking for cultural fit and excellent communication skills. However, working with a partner who vets top talent allows you to test first, then talk with the candidate to find out whether they fit the company’s data culture. This helps to address bias, as it is the skills test which first qualifies candidates.
Chisel Analytics can help you find the right data science talent for your company and provide you simple tools to assess, interview, and hire the talent you need. Our screening and assessment processes ensure you connect with the talent you need, when you need it. Whether you are recruiting for a specific need, team growth, or a change from your current direction, we can partner with you to find qualified data professionals with the skill sets you need.
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