An AI based talent acquisition and benchmarking for job
This work addresses a specific challenge for recruiters in the computer science industry by automating CV screening, but it is incremental as it applies existing NLP and ML methods to a new domain.
The authors tackled the problem of efficiently selecting the best CV from thousands for a job post in the computer science industry by proposing an AI-based methodology that matches skill graphs from CVs and job posts, using natural language processing and machine learning techniques.
In a recruitment industry, selecting a best CV from a particular job post within a pile of thousand CV's is quite challenging. Finding a perfect candidate for an organization who can be fit to work within organizational culture is a difficult task. In order to help the recruiters to fill these gaps we leverage the help of AI. We propose a methodology to solve these problems by matching the skill graph generated from CV and Job Post. In this report our approach is to perform the business understanding in order to justify why such problems arise and how we intend to solve these problems using natural language processing and machine learning techniques. We limit our project only to solve the problem in the domain of the computer science industry.