Designing a Data-Driven Job Search Strategy for Non-Majors — Hacking Job Hunting/Career Changes with Economics, Statistics, and AI

We understand the essence of the job market through concepts from economics and statistics, and use this foundation to redesign job-search and career-change strategies as a data-driven probability problem rather than relying on intuition or competing over credentials. Instead of accumulating more qualifications, we shift the game to a rational “market” by directly collecting and analyzing job-posting and company data with AI to identify markets and openings where the likelihood of success is high. By using AI as a tool built on core concepts from economics and statistics, we systematize application, interview, and job-search strategies, presenting a way to develop a data-driven approach to employment that even non-majors can understand. We also directly build a recruitment AI assistant that works 24 hours a day exclusively for me—using AI-based vibe coding accessible even to non-majors—which can be used immediately as a portfolio project in actual job preparation.