{"id":341022,"date":"2017-05-16T05:21:21","date_gmt":"2017-05-15T21:21:21","guid":{"rendered":"http:\/\/techcrunch.com\/?p=1489226"},"modified":"2017-05-16T05:21:21","modified_gmt":"2017-05-15T21:21:21","slug":"riminder-uses-deep-learning-to-better-match-people-to-jobs","status":"publish","type":"post","link":"https:\/\/people.utm.my\/asmawisham\/riminder-uses-deep-learning-to-better-match-people-to-jobs\/","title":{"rendered":"Riminder uses deep learning to better match people to jobs"},"content":{"rendered":"

<\/p>\n

There\u2019s absolutely nothing efficient about sorting through 30,000 resumes by hand. Recruiters spend months evaluating applicants\u00a0only to have great prospective candidates get lost in the pile. On the stage of TechCrunch\u2019s Startup Battlefield, French startup Riminder<\/a> made the case for how its deep learning-powered platform could augment recruiters \u2014 helping them better surface ideal contenders for job openings.<\/p>\n

Riminder generates candidate\u00a0rankings\u00a0for open jobs\u00a0by comparing applicant resumes against resumes from current employees and others in the world with similar job titles. Behind the curtain, Riminder uses a cocktail of computer vision and natural language processing to build profiles of what ideal resumes should look like for specific roles.<\/p>\n

\"\"Once a resume is processed, recruiters can view its strengths and weaknesses.\u00a0Riminder makes it easy to see\u00a0this information visually and to identify market trends, like the most popular schools to recruit from or the most common\u00a0skills applicants for a certain type of job typically have.<\/p>\n

The goal is to make sure recruiters have the information they need to judge candidates on both their ability to fit into company culture and their mastery of key\u00a0skills.<\/p>\n

When demonstrating Riminder\u2019s value to a potential recruiting client, the team often runs tests on historical data. This data makes it easy to compare the platform\u2019s automated short list with a human-generated list.<\/p>\n

\u201cWhen we compared results, recruiters found 3x more candidates they were interested in, they just\u00a0weren\u2019t\u00a0using the right keywords,\u201d\u00a0explained Mouhidine Seiv, founder of Riminder.<\/p>\n

Aside from helping recruiters sort through applications, the tool also has the potential to make hiring more fair.\u00a0Seiv told me that\u00a0some companies refuse to accept applications from international candidates simply because they don\u2019t feel comfortable evaluating\u00a0the applications. Because\u00a0Riminder has seen\u00a0resumes from around the world, regional variations are easy to accommodate.<\/p>\n

Another perk of Riminder is that it can automatically reroute applications to other open positions if it notices a better fit. This increases the likelihood that the right applicant will be considered for the right job.<\/p>\n

The objective of\u00a0Riminder isn\u2019t to replace recruiters. Humans still provide regular feedback on automated rankings and are ultimately\u00a0better suited to be the final gatekeepers, interviewing and issuing acceptance and rejection letters to applicants.<\/p>\n

The company participated in the CentraleSupelec Incubator\u00a0and is currently running betas with companies like Uber and Blablacar. It\u2019s currently marketing an enterprise-based offering charged on a per-user, per-year basis, a teams contact charged on a per-job title, per-month basis and a per-resume API offering.<\/p>\n","protected":false},"excerpt":{"rendered":"

\"\" There’s nothing efficient about sorting through 30,000 resumes by hand. Recruiters spend months evaluating applicants only to have great prospective candidates get lost in the pile. At TechCrunch’s Startup Battlefield, French startup Riminder made the case for how its deep learning-powered platform could augment recruiters — helping them better surface ideal contenders for… Read More<\/a><\/p>\n

\n<\/img><\/a> <\/img><\/a> <\/img><\/a> <\/img><\/a> <\/img><\/a> <\/img><\/a>\n<\/div>\n

\"\"\/ <\/p>\n","protected":false},"author":5817,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[25],"tags":[59,66,26],"class_list":["post-341022","post","type-post","status-publish","format-standard","hentry","category-technology","tag-media","tag-techcrunch","tag-technology"],"_links":{"self":[{"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/posts\/341022","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/users\/5817"}],"replies":[{"embeddable":true,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/comments?post=341022"}],"version-history":[{"count":0,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/posts\/341022\/revisions"}],"wp:attachment":[{"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/media?parent=341022"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/categories?post=341022"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/tags?post=341022"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}