Searching for an Employee

If a specialist with certain competencies is in demand in the job market, it can be difficult to find one, especially if there is a struggle with other employers for talented candidates. At such times, recruiting agencies may start offering their search services. That said, their involvement doesn't always speed up the process and can only mean one thing: finding a candidate will require additional funding for the recruiters' work. Especially since some specialized competencies may be difficult to find through standard search channels. It may require a more creative and specialized approach.

Unlike conversations with recruiters, when communicating with the Eontribe neural network, you do not have to hide your true desires for an employee. The information provided by the neural network does not go beyond the search, i.e. it does not lead to spam from organizations of this sphere or to social judgment. The only limitation in this regard is searching the profile of another person or organization for any illegal activity. This kind of thing is not allowed by the neural network.

The neural network will not offer options that do not fit your description and can in seconds reduce the choice of thousands of candidates to a short list of 5-10 people with the necessary certification. If necessary, it will compose individual qualifying questions and search based on all available information:

• criteria that are refined during the inquiry;

• all the candidates' references, diplomas and certificates;

• the most harmonious combinations of psychotypes for ideal teamwork, etc.

Case

Daniel is the head of a small IT company. One of his developers left a week ago, and Daniel devotes his time to talking to recruiters and conducting numerous interviews. The last of these showed that the candidate had absolutely no relevant skills, and the recruiter, due to her lack of understanding of the development processes, scheduled a useless half-hour meeting.

Almost giving up hope of finding an employee quickly, Daniel began signing up for specialized recruiting services. Luckily for him, he registered on Eontribe as well. Daniel began describing the request by describing his company, the projects they were working on, and the specific skill set a job seeker needed. The neural network asked a number of qualifying questions about the candidates' higher education requirements and their knowledge of advanced programming languages. As a result, a portrait of the requirements for the worker was created, and it was described by a specific provision of the query in relation to three indicators: speed, quality, cost.

The employee was officially hired after two days. He fit not only by his skills, but he also had similar interests and hobbies to Daniel and the other members of the team. To be finally sure of the right choice it was necessary to look through the diplomas and certificates of the candidates and conduct three interviews scheduled by the Eontribe neural network. Compared to recruiting agency statistics, this saved Daniel about 12 hours of his personal time for interviews and related organizational work. Also, Daniel has saved on the recruiting work process and can now offer better financial terms to his employees. Daniel has deleted other job-hunting apps from his phone.