Hiring industry has changed very much with the advancement in technology. Today, most Recruiters go through the candidates social profiles(LinkedIn, Facebook, Twitter, Github) along with the Resumes to figure out if the candidate is a good fit for the company.

All this sounds like one huge task which is generally spread over days depending on the number of candidates who have applied to the company.

Increasing trend in hiring the wrong Candidates for the job

One third of new hires quit their job after about six (6) months. (Source)

Increasing Unemployment Rate

It is forecasted that the number of unemployed people will reach more than 212m by 2019. (Source: Guardian)

The Current Process

General Hiring approach

Thus these recruiters just shortlist the candidates based on some hard filters like GPA, Years of experience etc. to shorten the list. This could potentially take hours to analyze and shortlist based on resumes. Moreover, they might have missed that someone who probably doesn’t have a good GPA but has a really good knowledge in the field of expertise.

What if this could be done in a better way and in a fraction of that time?

By employing certain AI technologies we can reduce the Man hours in recruiting and improve the accuracy in selecting candidates.

An AI engine can analyze the job description and tokenize the Key words and then analyze each candidate’s profile to match the skills, years of experience etc with the tokenized words in the Job description. This makes the Job of the Recruiter easier as they don’t have to spend their time analyzing hundreds of resumes.

And there’s more.(in the future)

The Company’s culture is very important for the candidate to thrive in the company. If the candidate cannot fit into the company’s culture he/she might not be able to contribute well in the company.

This is where the real power of Artificial Intelligence comes into play.

The Recruiter’s Company’s past hires and existing hires can be analyzed to figure out the type of people who would fit into the company. This can be done by creating a database containing the Social Data(LinkedIn, facebook, twitter, Github) of all the past hires and then performing Machine learning on this database.

Facebook/Twitter Data

Using Machine learning we can train a model on the type of people who would like to work for you by determining the type of people who are already thriving in your company. Facebook/twitter data can be analyzed to create a psych profile of a person. Qualities such as openness to experience, extroverted and agreeability/Team work can be determined using this data. Personality traits, leadership qualities can be determined based on the his social life using NLP on the facebook posts/ twitter feed.


Apart from using LinkedIn data to get a candidate’s work history and social data, using the candidate’s and company’s past hire’s LinkedIn data we can calculate a “Potential score” of the candidate based on how the past hires, similar to the candidate, have progressed in the company.


For a Tech related Job, the GitHub profile data also becomes important in deciding whether a candidate is a right fit for the job or not. The Candidate’s Github data such as repositories and Contributions to the GitHub community related to the Job description are analyzed to figure if the Candidate is a versatile programmer fitting the Job Description.

The Process using AI

Hiring Process flow using AI

Thus, Recruiter’s can accurately match their Job description with the relevant Candidates and save both the Candidate’s and Recruiter’s time and resources.

We, at Marax AI, are currently working on matching the candidates with the jobs based on their Resume and profile data. Using LinkedIn, Github and Social Data to train the model are still under active research and will go live soon.

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Also, if you’re interested, you can check out our demo on how we currently integrate Artificial intelligence into a Job Portal.