The labor market is rapidly evolving, and timely insights into in-demand skills are crucial for job seekers, recruiters, and policymakers. This paper presents Skillpulse, a real-time skill demand tracker that collects job postings via web scraping, extracts skills using NLP techniques, and predicts future trends with machine learning models. An interactive dashboard visualizes current and emerging skills, enabling stakeholders to explore opportunities, refine hiring strategies, and align education and training programs with industry needs. Experimental evaluation demonstrates accurate skill extraction, reliable forecasting, and scalable, near real-time performance.

real time skill demand,job posting analysis,labor market analytics,Natural Language Processing,machine learning,skill extraction,time series forecasting