Where to work: rely on data matching to improve recruitment efficiency

Absrtact: We see that today's Internet products have been very difficult to set a threshold from the functional level, the need to rely more on the user experience, cloud services, data services, strong architecture and communication protocols as the support, coupled with the emergence of a growing number of entrepreneurial companies, which

We see that today's Internet products have been very difficult to simply set the threshold from the "functional" level, the need to rely more on user experience, cloud services, data Services, strong architectures, and communication protocols as well as a growing number of entrepreneurial companies has increased the demand for such talent, but has always been Business and it talent online docking is not ideal, in the traditional recruitment site rigid functional framework, job search for both sides is a very inefficient thing. Recently, a company created by Hanbing, Gu Haijie and Yang Jintao hopes to improve recruitment efficiency by providing more comprehensive information and relying on data matching.

As shown in the picture, as a recruiting company, I need to fill in the position, type of work, work place, whether to accept telecommuting, and the skills required by the candidate. In the same way, job seekers fill in their own accounts and then match the data to each other--when I choose the "recommended" feature, the right person/company will be matched according to the algorithm. In addition, I can see in the "discovery" function of those who go to work in the company, these companies will be based on the number of attention in descending order to show, after I pay attention to them, if they have recruitment needs, I can be informed.

These features are designed to address the "discovery" of each other between job seekers and recruiters, but in reality "discovery" is simply the basic function of building an effective job-search platform. The real hurdle for online recruiting is "show"--although tagging matches can improve the efficiency of "looking at resumes" in traditional recruiting, however, both individuals and enterprises have too much to be "qualitative" and "quantitative" to describe the characteristics of the "social recruitment" the significance of the show: social circles, interests, resumes ... ... These dynamic, comprehensive information can portray a person's character more vividly.

So, as a recruiting site that is currently perpendicular to the IT field, it is also introducing the attribute of "social recruitment" in its own way--a column for "Social Information" in a personal resume, where users can add their own GitHub account or Dribbble account, Obviously, the two correspond to the social circle of the technician and the design/user experience staff. How many open source projects a user participates in, how much code they contribute, and how many design works are recognized ... To a certain extent to help job seekers to better show their ability. Hanbing told me that they would take this as a prototype and build a more socially-featured recruiting platform.

There is no denying that, as a start-up, where to go to work face a lot of growth problems: not enough data, very multi-functional in the embryonic stage, for the recruitment of enterprise social display program is immature (currently can add video introduction and microblogging) ... But I think it is based on the right product logic: Use the social information to make the user model, based on the data matching. A graduate of Carnegie Mellon, CTO Gu Haijie, who has been involved in large data and intelligent algorithms related to companies such as Google and Intel Lab, has also provided a reliable technical base for how it will grow. It's worth looking forward to.