YoungCapital creates breakthrough in machine learning in recruitment

Tuesday, July 11, 2017

YoungCapital has succeeded in making the recruitment process faster and more efficient through machine learning. An extreme achievement, because machine learning in recruitment is extremely complex.No other Dutch employment agency has been able to produce such an innovation. YoungCapital expects to provide more revolutions in the short term and, therefore, in this area, structural cooperation has begun with Leiden Institute of Advanced Computer Science (LIACS).

Source: YoungCapital

Optimize match between candidate and employer

Machine learning plays an important role in optimizing YoungCapital’s services. “If the computer takes over the most time-consuming work of our recruiters, they can spend more time on career counseling and coaching. And that’s just the beginning,” says Rogier Thewessen, one of the founders of YoungCapital. “Because in 2018, our candidates will be shown how much chance they’ll likely have for a particular job. We make suggestions for training that they can follow to increase their chances of shooting for that job. And we show alternative vacancies that make them a great opportunity. Our dream: less rejection, less disappointment and more happy candidates who get started in a job that really fits them. Our algorithm, YoungCapital Brain, will help us. “

Machine learning in recruitment: Recognizing patterns without pattern

Machine learning in recruitment is another free area. Owing to the space for interpretation, context and subjectivity, it is a very complex niche. Machine learning is about recognizing patterns. However, in the recruitment there are no patterns at first sight.

Machine Learning Fig. 1. Pretty simple issue (consumer buying / not buying in a store) versus complex issue (candidates selected / not selected in recruitment)

Srisai Sivakumar, data science and machine learning specialist at YoungCapital, explains: “Recruitment data is subjective. Think of the vacancy text, the CV and the motivation. Everybody writes in a different way, uses other words and emphasizes other things. YoungCapital Brain has to read all the same. However, a computer can not interpret as a human can, but reads words as numbers. Nuance and context we need to learn the computer. That is a huge challenge. Nevertheless, we have managed to achieve concrete results in the Netherlands with excellent accuracy. “

Inhouse solution

Machine learning is an absolute necessity in recruitment, Thewessen believes. YoungCapital’s database now has 4.8 million candidates. YoungCapital has been addicted to data since its establishment, but without a good search, it is possible to search data for a pin in a haystack in such a mountain. Algorithms can refresh this search. “First, we used a standard tool,” says Thewessen. “But we would not be YoungCapital if we did not think it should be better, smarter and faster. That is why we have developed our own self-learning framework with algorithm. YoungCapital Brain learns to recognize the behavior of our recruits and candidates and makes predictions based on it. In addition, machine learning also supports us in other business areas.”

Together with LIACS

The fact that YoungCapital takes major steps in this machine-learning niche, also professor Thomas Bäck, professor of Natural Computing, affiliated with Leiden Institute of Advanced Computer Science (LIACS): “I’m impressed with the robust results YoungCapital itself has Knowing with machine learning. YoungCapital has since become a dumb player in this field. Therefore, we are happy to work with them together. “For the Leiden scientists, the enormous mountain data of YoungCapital offers great opportunities for scientific research. The youth specialists’ data specialists, in turn, are pleased to have found a sound record. The LIACS does specialized research into parts of machine learning that are also of great importance to YoungCapital. Both parties are looking forward with interest and optimism to the future.

First result: selection time halved

Before YoungCapital Brain, every recruiter had to look at all the vacancies in order to select the best candidate. That costs a lot of time. YoungCapital Brain is now taking part of this process. It predicts based on data from the vacancy, CV, motivation letter and profile data which candidate is the best for a vacancy, and arranges them in order of suitability. The model has been so accurate that the best candidate in 99 percent of the cases is in the top half of the reactions. That’s why the recruiter is half the time. With almost 95 percent confidence, the best candidate in the top is 20 percent. That’s why the recruiter can take care of 80 percent of the time.

Accuracy Fig. 2. Accuracy YoungCapital Brain (top 50% and top 20%) deposited in time

About YoungCapital

YoungCapital believes in the power of young people. As digital natives, they hunt innovation at organizations. The recruitment specialist sees young people as the growth capital that every business needs. YoungCapital is committed to bringing it best to young people and companies. So they continue to stimulate each other to grow.