Job Title Predictor System

Abstract

In this paper, we propose a job title recommendation system using a combination of Natural Language Processing (NLP) techniques and machine learning. We implement a TF-IDF Vectorizer and cosine similarity to recommend jobs based on user inputs like skills, experience, industry, and role category. The system was built using Python and integrated into a user-friendly interface using Streamlit, enabling personalized recommendations. We evaluate the accuracy of recommendations and discuss potential improvements