MACHINE LEARNING BASED SKILL GAP ANALYSIS FOR INTELLIGENT CAREER RECOMMENDATION

Abstract

In the modern recruitment landscape, organizations receive a large number of job applications for a single position, making manual resume screening both time-consuming and inefficient. At the same time, many job seekers lack proper guidance to evaluate whether their resumes meet industry expectations or contain the required skills for particular job roles.

This research presents an AI-Based Resume Analyzer and Career Recommendation System designed to automate the resume evaluation process and assist users in improving their career prospects. The proposed system utilizes machine learning and natural language processing techniques to analyze resumes, extract relevant information such as skills, education, and experience, and generate meaningful insights.

Based on the extracted information, the system identifies skill gaps and provides recommendations for suitable career paths. This helps users understand the requirements of different job roles and improve their resumes accordingly. The system is implemented using ReactJS for the frontend interface, FastAPI for backend services, and Python-based machine learning models for resume analysis.

The proposed solution aims to simplify resume evaluation, reduce manual effort in recruitment processes, and provide intelligent career guidance for students and job seekers.