ResumeRevealer is an advanced tool designed for HR professionals, recruiters, and hiring managers to streamline the process of resume parsing and candidate evaluation. It offers a comprehensive solution to extract valuable insights from diverse resume formats, standardize job titles, and mine detailed skills from project descriptions.

Resume Parsing: Automatically extracts key information from resumes in various formats including PDF, DOCX, and HTML.

Job Title Standardization: Utilizes the O-NET database to standardize job titles and occupations for consistent taxonomy.

Skill Extraction: Mines detailed skills from project descriptions using advanced Natural Language Processing (NLP) techniques.

Resume Section Identification: Uses Named Entity Recognition (NER) to accurately identify and classify resume sections such as experience, education, skills, and more.

HR Professionals: Simplifies the screening process by providing accurate and standardized information about candidates.

Recruiters: Enables quick and efficient evaluation of candidate profiles, saving time and effort.

Hiring Managers: Facilitates better decision-making by presenting detailed insights into candidate skills and experiences.

Install ResumeRevealer with python >= 3.9

Tested on python 3.11

  git clone https://github.com/HariR1893/CyberX-ResumeRevealer.git
  cd CyberX-ResumeRevealer

Install the requirements.

  pip install -r requirements.txt

Download the Custom trained NER Model:

Download the pre-trained model -> click here save it in a : models/ner/JdModel

toolkit.ipynb