Big Data résumé crunching

Tom Breur

17 October 2016

Big Data is making entries in many areas of life. Since hiring and developing the best possible talent is the single most important management task, it is only natural that HR is jumping on the analytics bandwagon as well. Psychometric testing has long been one of the objective methods in their tool chest, and now Big Data are getting used to refine the candidate search process.

Many companies are trying to enhance their workforce to better “fit” the Big Data revolution. Sine Hal Varian said that statistician would be the sexiest job in the 21st century, they all want to hire statisticians. But as the pressure on the workforce increases, there are fundamentally only two ways to cope with the supposed shortage of talent: either you develop your own people, or you widen the net. I will assume that developing your own was already high on the “ToDo” list, so how do you widen the net?

By searching candidate resumes in much the same way a search engine scans the internet, you can determine the best possible fit between people’s background and experience, and qualifications that are required. If there aren’t enough statisticians, then what skills should we look for in resumes? Nowadays we see an influx of rather diverse skillsets that all seem to be qualified to become a data scientist. Experimental methodology, affinity with programming and databases, an investigative mind, critical thinking (and listening!) skills – a good data scientist brings a mixture of those to the table.

There is a fuzzy relationship between the multivariate search space of resumes, and a set of requirements that need to be met for various roles in a data driven organization. Machine learning has been proven to be particularly effective at finding those matches. And since computers can add value to this selection process, it only makes sense to leverage algorithmic technology for the most important decisions a manager can take: who am I going to hire next?


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