Hammad Hadi KhanFollow

Degree

Master of Science in Data Science

Department

Department of Computer Science

Faculty/ School

School of Mathematics and Computer Science (SMCS)

Date of Submission

Fall 2024

Supervisor

Saiyed Shahab Ahmed, Visiting Faculty, Department of Computer Science, School of Mathematics and Computer Science (SMCS)

Keywords

Recruitment Automation, Resume Parsing, Optical Character Recognition (OCR), AI in Hiring, Candidate Evaluation

Abstract

The recruitment process is an integral and resource-intensive aspect of every organization, but with advancements in technology, it has become possible to automate many of the manual tasks involved. This report presents a comprehensive solution for automating job application processing by utilizing Artificial Intelligence (AI) and Optical Character Recognition (OCR) technologies. The proposed solution analyzes and processes resumes, assesses candidate qualifications based on job descriptions, and provides recruiters with a suitability rating to streamline decision-making.

The system integrates OCR for parsing PDF resumes, AI for evaluating qualifications, and role-based access to ensure the recruitment process remains efficient, secure, and data-driven. The solution automates key tasks such as resume parsing, qualification analysis, and suitability evaluation, which minimizes the workload of HR teams and enhances the overall candidate experience.

By providing an automated and scalable approach to recruitment, this project aims to assist organizations in improving hiring efficiency, reducing manual errors, and enhancing data-driven decision-making. The report outlines the architecture of the system, describes its core components

Document Type

Restricted Access

Submission Type

Research Project

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