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 i
Analysis of resume through artificial intelligence
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.
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:
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.
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.
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.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| 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 |
| Total in (Rs) | 51440 |
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