STAR–CAREER Combined Dataset (v1.0): Interpretable Expert System for Verified Competency Tracking and Skill-Aware Job Recommendation

This dataset accompanies the research paper “An Interpretable Expert System for Verified Competency Tracking and Skill-Aware Job Recommendation using STAR and CAREER Algorithms.”It provides a reproducible benchmark for evaluating interpretable, logic-based frameworks for candidate shortlisting and job recommendation. The dataset includes 50 job postings and 100 candidate profiles, each characterized by proficiency levels (0–3) across five core technical skills: Python, SQL, Django, JavaScript, and HTML/CSS.All data were synthetically generated to reflect realistic distributions derived from BDjobs and LinkedIn observations. The dataset supports validation of the STAR (Skill-based Talent Alignment and Ranking) and CAREER (Connection and Recommendation Engine for Employment Recruitment) algorithms, enabling transparent, proficiency-aware reasoning without reliance on large training corpora.