EMPLOYABILITY HUB: Smart System for Skill Analysis and Career Prediction

Career guidance that relies on generic, manually administered advice cannot keep pace with a job market whose required skills change quickly. This paper presents Employability Hub, a web pipeline that takes a candidate from resume upload to a personalized career recommendation on a single platform: a Flask backend parses an uploaded PDF or DOCX resume with PyMuPDF and python- docx; the Google Gemini API extracts technical and soft skills and infers career interests; a timed assessment of 20 multiple-choice and 3 coding questions is generated from the candidate's profile, with coding questions executed through the Judge0 API; a skill-gap service compares the assessed profile against a target role; a roadmap service produces a learning plan; and a job-search step queries the Adzuna API for matching openings. We state plainly what is implemented and what is not: resume parsing, skill extraction, interest detection, the assessment engine, skill-gap analysis and roadmap generation are functional; coding-score submission and job-API integration are implemented but still under verification; and full-scale performance testing, UI testing and error-handling remain pending. No accuracy, latency or performance figures are reported because none have been measured; Section VIII fixes an evaluation protocol in advance of data collection so future numbers can be reproduced and checked rather than asserted.