Headhunting in AI
In our interview with Kelly, we discuss what it’s like to be a recruiter in this space and how a company can hire a data scientist. We also ask Kelly for her insights from her podcast, The Data Dig, to demystify data science.
Kelly explained that recruitment in this field is much more complex than any other industry. Firstly, there’s more demand for candidates than supply, so it’s hard to look for the right people. Another factor is that as technology evolves, the roles needed to work in this space does too. Kelly and Demetrios have both also found that a job role might be titled differently in different organisations. So, for example, a “data scientist” in one company might be labelled “data analyst” elsewhere.
Whilst there has been an increase in tech and AI in recruitment, Kelly prefers the human connection in this sector. Kelly has built up her network over the years in her career and can connect specific people where needs are. A human recruiter is also able to see past a CV and gain more insight into a person.
Using the example of LinkedIn Recruiter, Kelly explained that some HR technology might not be that accurate. When posting a job on LinkedIn, the Recruiter feature automatically vies a list of people they recommend for the job. Using NLP and other models, the technology can filter profiles and make suggestions. However, Kelly argued that the majority of the recommendations aren’t suitable for the job.
What have been your experiences with AI in recruitment? Let us know in our Slack channel!
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