How machine learning recruitment is helping companies to select the best talents.

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Posted On : 26th, May 2017


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How machine learning recruitment is helping companies to select the best talents.

26th, May 2017    -    Startup

Sometimes going the extra mile could be the most optimum choice ever. With technology at the epicentre of each and every step of our life. Its predictable to have an AI based recruitment. It so often happens that the HRs Offices are stacked with resumes and curriculum vitae that need to be matched with the skill, talent and the capability of a person. An HR has to take decisions that best suit the interests of the employees and the company.

 

About Seedlink

To ease the pressure of resume screening and phone interviews, Seedlink a company run by Robin Young who is a technologist and anthropologist, has used technology to track the human behaviour, skills and talents of individuals and rightly match them into a business that fits their capabilities. The project which is now a full time operating business has applied machine learning to recruitment. Precise mathematical tools have been developed that analyze how a recruiter can make choices and plan, using decision theory, decision analysis, and information value theory though all these tasks are mainly performed by a computer excluding the gigabytes of data that are transferred into the same machine. The machine learning algorithms and computer hardware have led to more efficient methods for training deep neural networks that can model complex data and match candidate’s requirements efficiently to the company’s demand.

 

How the Startup got started in China?

China produces seven million job-hungry graduates every year. When Seedlink conducted a case study with French Cosmetics and Beauty company L’Oreal while recruiting Chinese graduates in the year 2015 they realised a solution for the overcrowded applicants. They listed three open-ended questions to applicants who answered the questions on mobile and Seedlink analysed the applicants answers in five criteria including emotional stability, openness, agreeableness, extroversion and conscientiousness to evaluate applicants and predicted which applicants answer best fitted to LÓreal’s profile."In previous years we've really relied on CV screening as the first step, which is pretty common for a lot of companies," Jacob Bonk, recruitment director for L'Oreal China had commented. "When in fact what we're really looking for in students is raw talent. "The job was well executed by Seedlink.

 

Achievements

Seedlink won the eminent Best potential Human resources vendor award at the HR Executive Summit 2016 and China BOLE Award Ceremony, organized by Enfovia. They have often been appreciated by new age Entrepreneurs for their first of its kind of idea used in recruitment Platforms. Their customers include some of the renowned brands in the world like Coca-Cola, Lóreal, Accenture, Publicis to name a few and more than 35 paying customers.

 

‘Its time: how robots helps us find the career we want’ say their Rina Joosten, COO.

 

With Coca Cola, the company is now working to build interview A.I. (Artificial Intelligence) by modelling the judgement of existing staff over time to evaluate new hires. SeedlinkTech is working to solve the core challenge within deep learning in order to make video and audio analysis possible in future. Their goal is to launch a real-time tool for face to face interview to evaluate applicants at the end of the year.

 

The concept is well received in china where the population is highest in the world and providing better platform for candidates and companies to connect and explore the opportunities without any issues on place. Countries like India, China where the population is high and there is no scarcities of talents make it fitting for the company to explore the better future.  

 

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Anisha Francis

Holla! I love a lot of things of which eating, travelling and writing tops the list. I also believe “Life’s always gonna be jigga if you learn something from someone everyday.”



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