The recruitment process is very important for organizational success as it helps in identifying and selecting the right candidates for the job positions. With the rise of the online recruitment platforms, organizations are getting thousands of resumes for every job opening. Manual screening of resumes is time-consuming, labor intensive and frequently prone to human bias and inconsistency. Artificial Intelligence (AI) has become a powerful technology automating and improving many business processes including recruitment and talent acquisition. This research proposes an AI-Based Resume Analyzer which uses Natural Language Processing (NLP) and Machine Learning (ML) techniques to automate resume screening, skill extraction, candidate evaluation and job matching.

The proposed system takes the data of the resumes in the PDF and DOCX formats and analyzes the candidates’ qualifications, finds the technical and non-technical skills, and compares the skills with the requirements of the job descriptions. The system uses NLP techniques such as tokenization, stop-word removal, lemmatization, Named Entity Recognition (NER), and TF-IDF vectorization to convert textual data into meaningful information. Compatibility between the candidate profiles and Job requirements is calculated using Cosine Similarity. The system provides candidate matching scores and rankings to help recruiters make well-informed hiring decisions.