This document proposes a resume parser using natural language processing to help human resources departments efficiently extract important information from resumes. It involves using NLP techniques like named entity recognition to identify names, designations, universities, skills etc. from resume text and storing this structured data in a database. This helps automate the process of analyzing large numbers of resumes and identifying the most relevant candidates for jobs based on keyword matching between resumes and job descriptions. The system is able to convert resumes in different formats like PDF, DOC to text and standardize the information extraction and storage process.