Credit Risk Model Validation Quantitative Analyst information
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$51.6K - $66.2K
5% of jobs
$66.2K - $80.8K
14% of jobs
$81.9K is the 25th percentile. Wages below this are outliers.
$80.8K - $95.4K
21% of jobs
The median wage is $102.7K / yr.
$95.4K - $110K
11% of jobs
$110K - $124.5K
12% of jobs
$134.5K is the 75th percentile. Wages above this are outliers.
$124.5K - $139.1K
12% of jobs
$139.1K - $153.7K
11% of jobs
$153.7K - $168.3K
5% of jobs
$168.3K - $182.9K
4% of jobs
$182.9K - $197.5K
1% of jobs
How much do credit risk model validation quantitative analyst jobs pay per year?
As of Sep 11, 2026, the average yearly pay for credit risk model validation quantitative analyst in the United States is $113,881.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,500.00 and $140,500.00 per year, depending on experience, location, and employer.
A Credit Risk Model Validation Quantitative Analyst is a finance professional responsible for assessing and validating the accuracy, reliability, and performance of credit risk models used by financial institutions. Their work involves reviewing statistical methods, testing model assumptions, and ensuring compliance with regulatory requirements. By identifying model weaknesses and recommending improvements, they help institutions manage risk effectively and maintain sound lending practices.
To thrive as a Credit Risk Model Validation Quantitative Analyst, you need a solid background in quantitative finance, statistics, and programming, often supported by an advanced degree in a quantitative field. Proficiency with statistical software such as Python, R, SAS, and familiarity with regulatory frameworks like SR 11-7 and Basel guidelines are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret model results and convey complex findings to stakeholders. These competencies ensure models are robust, compliant, and transparent, safeguarding the organization's financial stability and regulatory standing.
Credit Risk Model Validation Quantitative Analysts often encounter challenges such as interpreting complex model methodologies, ensuring data integrity, and identifying model limitations or weaknesses. They must thoroughly assess both conceptual soundness and technical implementation, which can involve dissecting highly sophisticated quantitative techniques and large datasets. Collaboration with model developers and business stakeholders is essential to address findings, communicate technical issues clearly, and ensure regulatory compliance. Staying current with evolving regulatory standards and best practices is also a key aspect of the role.
What are popular job titles related to Credit Risk Model Validation Quantitative Analyst jobs?
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