I call It The BetaList for job seekers

#webdev #career #showdev #machinelearning

Looking at the recruitment industry, especially during this pandemic, there are loop holes in the talent sector. The most underrated talents are the fresh graduates, newbies and job seekers with little or no working experience. Atleast 25times per day, I see tweets like "Please retweet. My employer could be on your timeline". Upon checking the profile of the original poster, said poster is a newbie. There is a high chance that their tweets fall on deaf ears.

This also happens with some recruiters on LinkedIn whereby job seekers are required to comment with things like "Hi" if interested "in a job". Such posts end up having 1000+ comments. There is no way the recruiter ends up viewing each profile.

I am a software engineer with 7.5 years experience, specializing in compression engineering and A.I. In my experience, the newbies do a better job as opposed to the so called "professionals" and "senior engineers".

This loop hole motivated me to develop my new platform, KwickBox. I call it the BetaList for job seekers. My platform features the profiles, portfolio and front pages of job seekers (who possess little or no working experience). Said job seekers are also included in the daily newsletter which is viewed by recruiters, employers and other visitors.

The platform is entirely based on digital CV's and front pages. The front page is the first page every visitor sees upon arriving at your CV. Use this page to talk about what makes you special, further customize it using either WYSIWYG or markdown flavour, attach screenshots of previous work and more details.

With the use of Artificial Intelligence, employers are able to search for their ideal talent within seconds.

A bit about the A.I:
I can't divulge much information about the algorithm, but I'll give an overview.

As the platform features the portfolios and front pages of job seekers, we have a neural network studying patterns. This can include: job sector, skills, location(as indicated on their CV's), preferred job role and more. The neural network gets information via the front page of the job seeker and portfolio projects (for example software based) (using intelligent search and natural language processing).

Upon compiling the required information, the A.I scans through the employer's website (if it exists) or by keywords (for example, software development) and through our custom algorithm is able to provide atleast 20 newbie talents.

Employers are also able to get talents using the old-school search process should they wish to.

I plan on making a separate blog post with a bit of diagrams explaining parts of the algorithm. But this is pretty much the overview.

The platform also has premium features. I'll highlight the most loved one, which is CV Review. With this feature, send invite links to trusted individuals such as colleagues and they'll be able to provide a comprehensive CV review per section (for example, work experience, portfolio, etc). You'll get email notifications upon the completion of the CV review.