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USE CASE

Objective

The objective of the HR resume matching tool is leveraging AI to reduce or eliminate time-consuming tasks in the recruitment process. Recruiters can sort the applications in a fraction of time.  Profile Matching is a very important aspect when an application is received from the website and when the recruiter is searching for the best matching candidate from the candidate database. The AI-based tool, calculates the matching score and helps the recruiter to process the right candidate in the least time.

Outcome

The resume match score (0% to 100%) is based on how well your resume matches up with the job description you selected. Your match rate is based on your skills and many other criteria. The System automatically fetches the skills from your resume and try to match them with the skills of the job description. Therefore, the recruiter can easily decide on the candidate whether he/she is the right fit for the job or not. ML is leveraged to screen candidates and match their resumes with the job specifications at a blinding speed and stunning accuracy. It leverages recruiters’ feedback to build an effective algorithm to shortlist thousands of candidates based on their resumes. The AI helps in resume screening for a particular job opening and improves the representation of diverse applicants with a 100% bias-free algorithm.

Business Value

The HR resume matching tool, can reduce the efforts in recruiting and improve the accuracy in selecting candidates. The AI algorithm can analyse the job description, tokenize the keywords and then analyse each candidate's profile to match the skills, job title, experience, location, qualification, etc. with the tokenized words in the job description. This reduces the burden of the recruiter as they don't have to spend too much time analysing hundreds of resumes.

H2O's AI and Data Approaches

This solution  is powered by the H2O AI Driverless AI AutoML, and H2O.ai Wave. The data science approaches include genetic algorithm, advanced feature engineering, NLP, classification algorithms and algorithmic bias detection.

 

Resources

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