To thrive as a Model Risk Analyst, you need strong quantitative analysis skills, a background in mathematics, statistics, finance, or a related field, and experience in model validation practices. Familiarity with programming languages such as Python, R, SAS, and tools like Excel, along with knowledge of regulatory requirements such as SR 11-7, is typically essential; certifications like FRM or CFA can be advantageous. Excellent communication, attention to detail, and critical thinking are important soft skills for presenting findings and collaborating with cross-functional teams. Mastery of these skills ensures the integrity and reliability of risk models, supporting sound business decisions and regulatory compliance.