抛开简历来招聘,在人才学的眼里,申请就是一道问答题


当我们日常的吃饭、洗衣、出行都因移动端的普及发生深刻变革的时候,像招聘、找工作这样的行为,主要还是在PC端进行。原因除了要对职位和公司做大量的调查工作外,更主要的很难有体验糟糕过“在移动端写简历”。

那么,能不能换一个思路,让求职者用简历之外的东西申请工作?

人才学目前正在做的就是这件事。如果求职者正好在申请一家使用了人才学系统的公司,他会发现申请全程就是回答一个类似“如果你与一个意见相左的人沟通,你会怎样做以让这个沟通更加有效?”的问题。在他回答完问题后,人才学的QuestMatch系统从求职者答案中提取信息,根据求职者展现出品质与职位、公司的匹配度进行排序,供HR参考。

支持QuestMatch系统是自然语言处理技术,TalentBot的郭炎彬曾聊过,自然语言处理、数据挖掘准确度关键是要有足够的数据样本。目前人才学主要瞄准的是欧莱雅、联合利华这样的公司,单一次大型校招就有3万多条申请。

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事实上企业在招聘过程中一直有“气质筛选”这一环,过去主要由面试官的人工判断完成。人才学通过把这一环节前置,降低了移动端工作申请的门槛。大规模的公司都有自己的独立系统,过去学生每申请一个职位,就需要花1-2个小时填一遍网申系统。现在这个时间缩短到了20分钟左右。

另外,对于HR来说,这省去了简历筛选带来的巨大工作量。也在一定程度上能帮公司规避员工入职后因非技术原因离职带来的损失。人才学创始人Rina告诉36氪,这点对于创业公司也非常有价值,对于数据量不大的公司,人才学提供免费账户,之后随数据量增加提高收费。

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人才学未来主要方向是拓展大公司客户,后期不排除利用累积数据向求职者推荐职位的可能。创始人Rina之前创办过荷兰人力资源公司International Top Talent,另一位创始人的Robin有多年产品经验。目前正在进行Pre-A轮融资,此前收到过光速曹大荣和阿里巴巴郑允中的投资。

目前用自然语言处理技术来改进人才筛选机制的公司还有TalentBote成,前两着的主要着力点是简历分析。另外,以用测评系统服务大公司出身的测聘网已经在尝试向大公司落选者推荐其他职位。

原创文章,作者:饭遥

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