AI Career Role Recommendation System with Skill Gap Analysis, Career Progression, and Salary Simulation Using Resume Semantic Analysis

Abstract: Due to changing job market trends, differing skill sets, and the absence of personalized career counselling and guidance systems, it has become difficult for job seekers or students to choose their path. Therefore, an AI-Based Career Guidance and Role Recommendation System is proposed in this project, which performs smart resume semantic analysis to recommend career roles based on skills, educational qualifications, amount of experience, and professional interests. Resume parsing and Natural Language Processing (NLP) based techniques are used to convert tacit knowledge contained in a candidate’s resume, which is an unstructured collection of words, into structured information about technical skills, educational qualifications, professional certifications, and work experience. TF-IDF (Term Frequency – Inverse Document Frequency) vectorization is used to convert a resume into a high-dimensional feature vector. Cosine similarity based semantic similarity algorithms are then applied to map these candidate’s profiles to role descriptor templates and industry-specific competency frameworks of matching job roles. The system includes a Skill Gap Severity Index to identify missing and underserved skills for target roles, a Customized Learning Plan Generator to recommend upskilling pathways, a Career Progression Simulation to visualize different career paths, and a Salary Range and salary levels. Peer Benchmarking System compares a users and Resume Improve intelligence improves resumes by analyzing them to identify missing skills and errors instead of only giving a score. profile with similar candidates having the same degree and experience level. The proposed system is based upon semantic profiling, similarity modeling, predictive career analytics, and resume improvement intelligence, providing students, freshers, and job seekers with personalized, accurate, and actionable recommendations to make informed career decisions and achieve sustainable growth in their respective careers.

Index Terms: Career Role Recommendation, Resume parsing, Skill Extraction, TF-IDF, Semantic Similarity, Artificial Intelligence, Salary Range & Simulation, Natural Language Processing (NLP), Skill Gao Severity Index, Skill-Based Career Mapping.