Data-Driven Career Strategy Design for Non-Majors - Hacking Employment and Career Changes with Economics, Statistics, and AI

Understand the essence of the job market through economic and statistical concepts, and redesign employment and career-change strategies as data-driven probability problems rather than relying on intuition or "spec" (credentials) competition. Instead of simply accumulating more credentials, this strategy shifts the "playing field" to a rational recruitment market by using AI to directly collect and analyze job postings and corporate data to select markets and openings with a high probability of success. By utilizing AI as a tool built upon core economic and statistical concepts, we systematize document, interview, and application strategies, presenting a way for even non-majors to develop a data-driven employment mindset. Furthermore, we provide a method for non-majors to directly implement a 24-hour AI recruitment assistant—which can be used immediately as a portfolio piece—through AI-based "Vibe Coding."