TMP Worldwide, a global leader in talent acquisition technologies, announced they’ve released the TalentBrew Job Classification engine – a proprietary machine learning method of automatically turning the millions of jobs, and hundreds of millions of candidates who interact with those jobs across the TalentBrew network, into an anonymized and common data set that can be leveraged by all TalentBrew customers. The collective intelligence of the data produced will be used to power insights, benchmarks and to drive recruitment marketing and process automation across the TalentBrew software platform.
Serving as a machine learning model that identifies and leverages commonalities across the millions of jobs that run through the platform – and the associated candidate data – the TalentBrew Job Classification engine will act as a core component to power artificial intelligence and functionality on TalentBrew.
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“As we continue to integrate automation into the ways talent acquisition teams’ source and recruit, both the quantity and the quality of that data that powers the insights and machine learning that drive automation becomes critical,” explains Todd Maycunich, VP Product Innovation at TMP Worldwide. “The opportunity that comes with a software platform with the depth of data that TalentBrew has is the confidence that that data can be used to automate particular recruitment marketing tasks. Thanks to the incredible work of TMP’s Data Science team, our new job classification engine is helping create new and unique value for employers using the TalentBrew platform.”
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TalentBrew Job Classification was conceived through TMP Labs, TMP’s dedicated research and development group. “The commitment we’ve made to TMP Labs is driving our company forward,” said Michelle Abbey, President and CEO of TMP Worldwide. “Their research, concepts and overall technological intelligence – both inside and outside the recruitment industry – is helping us lead a market where automation and AI will play an increasing role in the way that employers and candidates connect.”
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