“Recruitment while we could apply technology to the remaining

“Recruitment
is typically a high touch business. You need to understand in-depth what each
company does, what their requirements are, find candidates that match their
needs, check profile quality, get them to solve coding challenges, evaluate the
solutions, get companies to shortlist them, set up interviews, understand if an
offer will be made, make sure the candidate joins once they accept the offer,
and finally follow up to get payments on time.” Mr. Nair states that

 “As one can imagine, there are a lot of human
touch points here. However, we felt the value of human interaction is ten times
more for some touch points while we could apply technology to the remaining 90%
of the processes”.

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Mr. Nair and team were now building in-house technology
driven machine learning modules to automate things that were being carried out
manually.

As Mr
Nair recalls

“We
didn’t start by applying technology to everything though. We started by doing
things manually, understanding what works and then picking up problems to solve
one by one.”

When Geektrust
started, Mr. Nair and tem used to look at each profile to understand coder’s
core skills, their interests, how active they are, what sort of roles will fit
them and which companies would be a match for them. Geektrust automated this
and created a metadata for the hundreds of developers who registered with Geektrust,
on a weekly basis.

“We’ve
used classifier systems (falling under the larger umbrella of machine learning)
to implement this.Usual problems with the coders are that they proclaim they
know everything on their CV.”

As  Mr. Nair speaks

“We have folks who fill in their
profile saying they know java, android & testing. So what is their core
skill? Is it Mobile development or backend development?”

Such
assessments were carried out by using ‘Machine Learning’ by Geektrust and were
trying to bring some uniqueness to the hiring industry. Geektrust wanted to
provide niche service to the coders and firms (do we need to elaborate) –
define Machine Learning:

 

 

Mr. Nair
says

“We were
applying technology to recruitment.  We look into the aspects where we should apply
the right technology to enhance the recruitment phase.”

Geektrust was getting matured in terms of
employers, all queries from employers were looked into and taken with priority
and solved.

Geektrust
got about 500+ candidates expressing interest monthly. Qualifying all of them was
a challenge. To make sure they’re a fit for each other was a big question? Coders
needed to be tested with respect to their skill match as well as quality
perspective. Mr. Nair recalls that

“We used to do this
manually but now we’ve automated this. Yet again, machine learning along with
implementing a business rule engine helped us solve this.”