Authors: Gudimella Akhilesh, Peruri Karthik Sai, Kunburu Manikanta Reddy, Dr. Atul Kumar Ramotra
Abstract: Career decision-making among engineering students is often influenced by trends rather than a proper evaluation of individual skill sets, leading to skill–career mismatch. This project presents CareerLens, an explainable skill-based career recommendation system designed to guide students in selecting suitable academic streams and job roles. The system analyzes user-provided technical skills along with proficiency levels, maps them to predefined career requirements, and computes readiness scores to generate personalized recommendations. Additionally, it identifies skill gaps and suggests improvements to enhance career readiness. By emphasizing transparency, interpretability, and skill-driven guidance, CareerLens aims to bridge the gap between student capabilities and evolving industry demands.
DOI: https://doi.org/10.5281/zenodo.19550142
