For each recruitment, companies take out online ads, referrals and go through them manually.
Companies often submit thousands of resumes for every posting.
When companies collect resumes through online advertisements, they categorize those resumes according to their requirements.
After collecting resumes, companies close advertisements and online applying portals.
Then they send the collected resumes to the Hiring Team(s).
It becomes very difficult for the hiring teams to read the resume and select the resume according to the requirement,
there is no problem if there are one or two resumes but it is very difficult to go through 1000’s resumes and select the best one.
To solve this problem, today in this article we will read and screen the resume using machine learning with Python so that we can complete days of work in few minutes.
2. What is Resume Screening?
Choosing the right people for the job is the biggest responsibility of every business since choosing the right set of people can accelerate business growth exponentially.
We will discuss here an example of such a business, which we know as the IT department. We know that the IT department falls short of growing markets.
Due to many big projects with big companies, their team does not have time to read resumes and choose the best resume according to their requirements.
To solve this type of problem, the company always chooses a third party whose job is to make the resume as per the requirement.
These companies are known by the name of Hiring Service Organization. It’s all about the information resume screen.
The work of selecting the best talent, assignments, online coding contests among many others is also known as resume screen.
Due to lack of time, big companies do not have enough time to open resumes, due to which they have to take the help of any other company.
For which they have to pay money. Which is a very serious problem.
To solve this problem, the company wants to start the work of the resume screen itself by using a machine learning algorithm.
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