Job Board Journalist: Machine Learning & Job Boards

Peter Weddle

Goggle’s Cloud Jobs API brings the power of machine learning to job search. Job seekers don’t know what they don’t know about the labor market, so the technology acts as a job search assistant by helping them get better results when searching a job board’s database. While that’s obviously good for the job seeker, it also benefits the site … and it’s only the first in what could be a whole generation of machine learning applications that add value to job boards.

Google’s new API gives job seekers the ability to tap the experiences of millions of other job seekers like them to find the greatest number and range of employment opportunities for which they might be qualified. They don’t have to be an HR expert or an occupational scientist to figure out what jobs their skills and knowledge could potentially enable them to fill. And, they don’t have to know how to compose sophisticated Boolean search strings to run down all the possible alternative expressions other people use to identify and describe those jobs.

Google does all of that for them. By fusing the terabytes of data it has archived from previous job searches with its world class analytical and search algorithms, it has taught its “machine” how to help job seekers get better results from their queries of jobs databases. The machine has learned, for example, what a sales professional with 10 years of experience will actually be looking for when they search for a Sales Manager opening. It knows what job titles their peers have used in their searches for the same kind of job and what other types of jobs they found for which they were qualified and applied.

The end result is two satisfied customers. The job seeker finds the employment opportunities they want plus those they hadn’t thought of or even realized might be relevant. Employers will get more applicants per posting and those applicants are likely to be an equally or even better fit with their expressed requirements than those they received previously. All other things being equal, that’s likely to lead to a stronger site brand and better bottom line performance.

But is that all that machine learning can (and probably will do) for job boards?

Not even close.

Here are a couple of other potential machine learning applications that could impact job boards.
• A personal assistant. In addition to what they don’t know they don’t know about the job market, job seekers also often don’t know what they don’t know about themselves. They are clueless about what work environment they most enjoy and in which they are most likely to excel. For example, are they most comfortable with a flat or a hierarchical organization and do they respond best with a lot or a little direct supervision.

Why should job boards care? Because such personal factors have a huge impact on performance, and whether it’s fair or not, job boards are often faulted when new hires fail to perform at the expected level. Having a personal assistant built with machine learning, therefore, can help job seekers make smarter decisions when evaluating job offers, and those smarter decisions will help keep both them and site customers happy.

• A career assistant. Job seekers also don’t know what they don’t know about effective career self-management. They are literally on their own in today’s workplace, yet the vast majority are clueless about how best to deal with critical career issues. They don’t know how to determine the right time to look for a new job that will advance them in their field or if they are qualified and positioned to compete for the next step up in their company.

When job boards can leverage machine learning to offer such counsel, they will have a resource that is valuable to both workers who are actively looking for a new job and those who are not. As a result, the sites will be able to attract even the most passive high caliber prospects – individuals who seldom visit corporate career sites or use search engines to look for a job – and, in the process, set themselves up as uniquely credible sources of the very best talent.

Machine learning is often linked with artificial intelligence and thus seen as the stuff of science fiction. Google has proven, however, that there is already at least one useful application of the technology, which can directly benefit job boards, and it is possible to imagine others that could be developed in the not-too-distant future.

Food for thought,

The Job Board Journalist by Peter Weddle is brought to you by TAtech: The Association for Talent Acquisition Solutions.

Mark Your Calendars! TAtech’s 2017 events include:
• September 27-29, 2017 Denver: The TAtech Fall Congress & Deal Center, with The World Job Board Forum and the 2017 ReSI Awards Gala.
• March 13-14, 2018 Dublin, Ireland TAtechEurope 2018, The TAtech Industry Congress in Europe – the premier event for recruitment technology thought & business leaders worldwide.
• April, 2018 in Las Vegas: The TAtech Spring Congress & Deal Center. See the 2017 conference details here.
• June 5-6, 2018: The TAtech Leadership Summit on Programmatic Ad Buying. See the 2017 conference details here.

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