Hiring the most capable students to serve in the RA role should be a top priority for housing departments due to their critical role as front-line student success employees. The effort to identify and hire RAs typically includes a substantial investment of personnel resources in hiring processes, where candidates are typically evaluated across multiple components (e.g., applications, group process, interviews) spread across several days or weeks. Assuming that RA hiring processes should ultimately reveal the candidates who are most likely to demonstrate the strongest performance in the job, this study explored how candidate scores may predict performance under different scoring mechanisms. By using various weighted component scores, this study reverse-engineered the hiring process at one institution through two annual hiring cycles. The primary analysis included nearly 400 simple linear regressions with different component weighting combinations. At each step of the analysis, the results revealed increased significant prediction of future job performance using specific weighted component scores. Throughout, discussion about structural and mechanical bias within hiring processes is considered. Implications for practitioners to increase hiring process intentionality and recommendations for future research are shared. [Discussion questions developed by Denise Davidson along with Cody Deitz, Paige Friesema, and Bryson Purcell.]