If we could do everything on our own, we'd do it. But we can't, so we hire professionals from our fields of requirements. Striking a balance between employer rights and employee rights, the current hiring process is highly streamlined and performed by specialists.
Then why do we still keep hearing tales of bright prospects such as creator of Homebrew getting rejected by Google and the founder of Ethereum failing to get an internship at Ripple? Does it lend credence to the theory that the hiring managers are the bottleneck?
Actually, No.
The hiring process, despite its evolution lacks the ability to provide recruiters sufficient information on the relevant skills of the candidates.
(Unethical life hack #1) : When applying for a position, create a fake job listing for the same profile, collect all resumes, and take their best bits to craft a winning resume.
Good for you. But bad for the company.
Most hiring managers use arcane text parsers that are basically a find and highlight tool. For example, if a recruiter wants to look up Java developers and your resume says that your hobbies include drinking Java coffee, guess what, you're shortlisted too.
Skill matching should be based on the candidate's past relevant profile and not just rely on cheat-friendly online skill tests or test-by-whiteboard during in-person interviews. But recruiters are bound by limited data points. Without sophisticated tools at their disposal, the recruiters are forced to either:
Call in a large number of candidates for screening interviews
Screen with the broad brush that are the text parsing screening software
(unethical life hack #2) : If applying for a python developer profile, you'll be asked to reverse a string. Instead of writing a function, simply use a negative step in the string slicer.
Chances are that the recruiter is not as adept at programming as technical managers and will send you to the next round because you solved their puzzle with a very short code.
To conclude, you can either stick to the existing leaky recruitment system or move ahead with the times to properly leverage the technologies at hand to make lives easier. Automation, AI, and Machine Learning have arrived to take the pain out of the recruitment process.
All that is left is the skillful application of matching algorithms based on candidate data. Thus, the recruiters with larger datasets will tend to match recruiters with candidates with greater accuracy and with a higher success rate.
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