Analysis of resume through artificial intelligence

Project Title

Analysis of resume through artificial intelligence

Project Area of Specialization Artificial IntelligenceProject Summary

An integrated company oriented e-recruitment system was implemented based on the proposed scheme. Our system was employed in a large-scale recruitment scenario, which included three different offered positions and 100 job applicants. The application of our approach revealed that it is effective in identifying the job applicants’ extraversion and ranking them accordingly. There are two possible ways of analysing these results. By looking at the scores summary data frame, hiring managers can determine how many key terms were included in each concentration area from a given list. On the other hand, by looking at the pie chart, hiring managers can identify my main concentration area and determine to what extent I could be considered for jobs related to other areas. The scores will be highly influenced by the number of keywords in each concentration area, reason why it is highly recommended to distribute keywords uniformly to avoid undesired bias on the results.

Project Objectives

Freeing Up Recruiters Time

On average, every job post receives about 250 candidate applications. If a recruiter spends about 2 minutes for screening a resume, it is 500 minutes a day. Resume screening software can do that in 2 seconds. Yes! in 2 seconds.

In addition to that, using AI for resume screening can rank these candidates based on your hiring pattern. AI can screen resume like a domain expert. It would screen resumes contextually. So, the shortlisting of candidates happens right away. Recruiters do not have to screen a pile of resumes one by one. They could find the best matching resumes soon.

With more time available, a recruiter can spend their time talking to the most promising candidates and increase their chance of engaging the right talent faster.

Engage Best Candidates

Recruiter’s process resumes in the order they receive it or find it. Many times they either receive applications that are not relevant or when they search for candidates on job boards, they are often misled by error-prone keyword matching techniques.  e.g. when recruiters are searching for Oracle developers they end up finding many Java developers because both kinds of candidates have mentioned pl-sql on their resume. Similarly, it happens for Financial Analyst vs Data Analyst or Company Secretary vs Personal Secretary. The examples are countless.

Basically, a recruiter may end up spending a lot of time engaging non-relevant candidates. When you have already spent days in engaging not so good candidates, you may tend to believe those good candidates are difficult to find. It is then you start thinking about making compromises.

AI For Resume Screening Can Reduce Unconscious Bias

Believe it or not but we tend to have an unconscious bias towards many things. Recruitment is no exception. Many times a hiring manager or a recruiter makes a decision by just reading the name of a candidate. Candidate demographics such as gender, race, religion or region can fuel such unconscious bias.

The use of AI for resume screening can help in eliminating such biases. Influential factors such as demographic details can be completely ignored while screening candidates.

Diversity is an important factor in an organization’s success. Hence it is important to address such unconscious biases that may restrict diversity at your organization.

Final Thoughts

In a very competitive talent-driven market you want to reach quality candidates faster and engage them better. Social media platforms are working as fuel to attract more active and passive candidates. With the volume of the candidate, applications are always going up, you need an approach like using AI for resume screening to quickly identify best candidates from the rest. Here is a useful reference guide on using ai for resume screening.

Project Implementation Method

Project Implementation Method:

1. Skills Testing: The number one priority for most employers out there is simply – whether the candidate can do the job or not. However, this is not something that you will be able to tell from resumes, reference checks (not entirely, at least) and looking up your candidates online.
2. Resume Screening: Next on the list – a more old school technique. Going through resumes is the oldest method of determining if someone is the right fit for the job, and it starts with the resume. Although resumes aren’t the best indicator of a candidate’s skills, they’re one of the key elements hiring and they don’t seem to be going away any time soon. Here’s some of the information you can get from a resume while screening candidates.
3. Cover Letters: Resumes are a great way for candidates to present themselves, but they can be rather limiting. If you want them to tell more about who they are early on, you can ask for a cover letter along with the resume as part of the application process. Besides showing off their writing skills, here are a few more things you can find out about applicants from the cover letter.
4. Applicant Tracking Systems: At some point in time, HR professionals realized that going through resumes manually just takes too much time and work, and applicant tracking systems came to be. These software solutions automatically run through resumes and find the best candidate on your behalf. They’re an essential element of the hiring process in enterprise businesses that get a large volume of applicants per position. However, research states that only 40% of all employers use applicant tracking systems.
5. Reference Checking: Another old-school candidate screening technique, reference checking is an essential part of making an educated decision about your new hire. After all, what better indicator is there of how a candidate performs than checking their performance with previous employers?

   If you think that reference checks are a relic of the past in the HR world, you’re very much mistaken. In fact, 8 out of 10 HR professionals conduct reference checks for new job applicants. Interestingly enough, the more senior the position, the more likely they are to do a reference check.

Benefits of the Project

A resume screening software enables recruiters to wade through an ocean of resumes (especially during high-volume recruiting) to find the perfect candidates that match the job requirements. It filters applications based on skills, education, experience or anything that is a requirement for an open role.

1. Parse and deep search resumes: Every resume that’s uploaded to Freshteam gets parsed and its data populated in profiles. This way, resume data becomes something that you can use to filter candidate profiles. Want to pull up a list of developers in your applicant tracking system who’ve worked with Alexa? Piece. Of. Cake.
2. Pre-screen for tech interviews: Another greate way to search candidates, especially during technical rounds is by using pre-screening tests using pre-assessment test providers such as HackerEarth, HackerRank, or Codility. These are quick, unbiased, and can be conducted in bulk.  Freshteam integrates with various pre-assessment tests providers to offer a seamless interview experience.
3. Cut the chase with application forms: When you are looking for something specific in your candidates, let’s say, their visa information or their willingness to relocate, links to their social profiles or anything else that might not fit into a standard resume, just shoot the questions on a custom application form. Then, you can filter for your ideal candidates based on their responses, in a few clicks.
4. Screen as a team: Get everyone invested in the screening process, right from day one. Your hiring team can participate in the shortlisting process and voice their opinions through comments and stars. The team will be able to access all the information you have at hand helping you make quick decisions and accelerate resume screening.
5. Save your favorite screened candidates for later: Found an exceptional candidate who did not fit into any of your open jobs? Don’t let your heart ache. Freshteam allows you to save them for later by archiving them to a talent pool.

Technical Details of Final Deliverable

When a job opening receives 250 resumes on average and 75% to 88% of them are unqualified, it’s no wonder the majority of talent acquisition leaders still find the hardest part of recruitment is screening the right candidates from a large applicant pool. Intelligent screening software automates resume screening by using AI to learn from historical hiring decisions to improve quality of hire and reduce employee turnover. Screening software that uses AI learns the job qualifications based on its description and learns what good candidates look like based on your historical hiring decisions.

The AI analyzes your existing resume database to learn which candidates moved on to become successful and unsuccessful employees based on their performance and tenure.

The software then applies the knowledge it learned about employees’ experience, skills, and other qualifications to automatically screen, rank, and grade new candidates from A to D or Red, Yellow, and Green.

Final Deliverable of the Project Software SystemCore Industry ITOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Decent Work and Economic Growth, Reduced Inequality, Sustainable Cities and Communities, Responsible Consumption and Production, Peace and Justice Strong InstitutionsRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	51440
Google API's	Equipment	2	10000	20000
Web Hosting	Equipment	1	10000	10000
Web Template	Equipment	1	5000	5000
Python 3.5, bootstrap 4 complete course	Equipment	3	5000	15000
A4 Pages	Miscellaneous	50	5	250
Rough Copy	Miscellaneous	1	200	200
Internet Charges	Miscellaneous	1	990	990