AI Assistant Recruiter

Abstract

A CV (Curriculum Vitae) or Resume is used to make a first impression on a prospective employer. It shows a candidate’s essential information, i.e., background, skills, and education so that a potential employer is quickly able to see how your past experiences can add to a corporation’s success. A well-crafted resume immediately demonstrates an applicant's suitability and lands that candidate on the interview. As the name of our final year project title “AI Assistant Recruiter” suggests, our aim or goal is solving the same problem or struggle of the recruiters by providing them or an organization, an Automated or Intelligent Modern software. This software or tool will help in “Filtering or Screening” bunch of CVs (Curriculum Vitae) automatically on the basis of the customized filters or checks such as filtering the CVs or candidates on the basis of their city, age, gender, marital status, religion, residence or location, CGPA, institute, certifications etc; given or mentioned by an organization. We also aim or committed to providing an efficient system or tool which will help define or extract the “Hiring Pattern” of an organization and then applying the same pattern to obtain the required data from CVs and filtering them accordingly. It will surely help in saving a lot of time and struggle of an organization or even can replace the job of the recruiter with more efficient and error-free work. Conventionally, human recruiters manually perform the screening of CVs and resume according to the job specification to find the best fit, which is tedious and arduous. Machine learning provides us with the opportunity to build more valuable programs in less time. This ML program reduces management staff, cost per hire, and makes us proactive rather than reactive. It determines the optimized talent pool and from that selects the qualified candidates. Using AI, algorithms and formulas can be optimized to the user, ensuring that the best employee is perfectly matched to the right place. Place, wage, academic history, career backgrounds, culture and many more will be the parameters for selecting applicants. We are committed to delivering a transparent and efficient system which can extract the previous hiring pattern of an organization and deduce former intelligence, but only better.