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Model Validation Quant Jobs (NOW HIRING)

Frost Bank

Model Validation Analyst II

San Antonio, TX · On-site

If so, being a Model Validation Analyst II with Frost could be for you. At Frost, it's about more ... Master's degree in a quantitative field such as Mathematical Finance, Financial Engineering ...

AIG

AI Model Validation Lead, GenAI

Atlanta, GA

$210K - $280K/yr

Design and execute comprehensive model validation strategies, including quantitative and qualitative assessments. * Review model development documentation, code, and datasets for correctness ...

Keybank

Quant Analytics Assoc - Model Risk

Cleveland, OH · Hybrid

$68K - $103K/yr

Perform hands-on quantitative model validation/review under supervision. This includes testing the model's conceptual soundness, data accuracy, methodology, and ongoing performance through techniques ...

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All JobsModel Validation Quant Jobs

Model Validation Quant information

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How much do model validation quant jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for model validation quant in the United States is $52.00, according to ZipRecruiter salary data. Most workers in this role earn between $39.42 and $63.22 per hour, depending on experience, location, and employer.

What is the difference between Model Validation Quant vs Model Risk Analyst?

AspectModel Validation QuantModel Risk Analyst
Required CredentialsQuantitative degrees (Math, Finance, Engineering), certifications like CFA or FRMSimilar credentials, often with risk management certifications
Work EnvironmentQuantitative teams, model validation departments, financial institutionsRisk management teams, compliance departments, financial firms
Industry UsagePrimarily in banking, asset management, hedge fundsAcross banking, insurance, asset management
Common Search/ComparisonModel Validation Quant vs Model Risk Analyst

The Model Validation Quant focuses on independently testing and validating financial models to ensure accuracy and compliance. The Model Risk Analyst also assesses models but often has a broader role in identifying and mitigating overall model risks within an organization. Both roles require strong quantitative skills and industry experience, but the Validation Quant is more specialized in model testing, while the Risk Analyst covers wider risk management functions.

What are some of the main challenges a Model Validation Quant faces when assessing complex financial models?

One of the primary challenges for a Model Validation Quant is evaluating the robustness and accuracy of sophisticated models, especially when underlying assumptions or input data are uncertain. This often requires a deep understanding of both quantitative finance and programming, as well as the ability to communicate findings clearly to stakeholders who may not have technical backgrounds. Additionally, staying updated on regulatory requirements and best practices is crucial, as validation standards frequently evolve. Collaborating effectively with model developers and risk managers is also key to ensuring models meet both business and regulatory expectations.

What are Model Validation Quants?

Model Validation Quants are quantitative analysts who assess and validate the financial models used by banks and financial institutions. Their main job is to independently review models for pricing, risk management, and capital calculation to ensure they are accurate, robust, and compliant with regulatory standards. They identify potential model weaknesses, suggest improvements, and document their findings. This helps organizations manage model risk and maintain regulatory compliance.

What are the key skills and qualifications needed to thrive as a Model Validation Quant, and why are they important?

To thrive as a Model Validation Quant, you need a strong background in quantitative finance, statistics, and mathematics, typically with an advanced degree such as a Master's or PhD. Familiarity with programming languages like Python, R, or MATLAB, and experience with risk management systems and model validation frameworks are crucial. Attention to detail, critical thinking, and clear communication help distinguish top performers in this field. These skills ensure accurate model assessments, regulatory compliance, and effective risk mitigation in financial institutions.
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What job categories do people searching Model Validation Quant jobs look for? The top searched job categories for Model Validation Quant jobs are:
Model Validation Quant jobs near you
Infographic showing various Model Validation Quant job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, 1% Temporary, and 2% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution, with an average salary of $108,152 per year, or $52 per hour.
Model Validation Analyst

Model Validation Analyst

First Electronic Bank

Salt Lake City, UT • On-site

Full-time

Re-posted 20 days ago

Job description

Job Type
Full-time
Description
At First Electronic Bank (FEB), we are driven by the purpose to make credit accessible to everyday Americans, and their businesses. Partnering with some of the most innovative FinTech companies in the nation, we offer a wide range of consumer and commercial credit products on a national basis. Offering revolving lines of credit, private-label credit cards, installment financing programs and more, FEB's engages with strategic, collaborative partnerships, promoting services and products to provide the most beneficial consumer and commercial financing solutions.
The Model Validation Analyst plays a critical role in ensuring model integrity, regulatory compliance, and sound risk management practices. This role reports to the Head of Credit Risk and Portfolio Analytics Credit and supports the Bank's strategic partner program by reviewing statistical models used in underwriting and assessing overall model risk across partnerships.
What You'll Do:
  • Review third-party model validation documentation for conceptual soundness and alignment with applicable regulatory guidance.
  • Assess and challenge credit models and underwriting strategies used in loan origination.
  • Maintain a comprehensive inventory of all models used by the Bank, including underwriting, fraud, and marketing models.
  • Evaluate model performance monitoring practices and ensure appropriate tracking of key risk indicators.
  • Partner with Compliance, Legal, and Strategic Partner Management teams to ensure models meet applicable regulatory and internal policy requirements.
  • Prepare reports and present model risk metrics to the Bank's Credit Committee.
  • Monitor and test credit origination strategies to validate accuracy and consistency of credit decisions.
  • Conduct model and credit risk due diligence for prospective fintech partners.
  • Participate in or lead initiatives to enhance model risk management processes and improve overall risk oversight.

Requirements
What We're Looking For:
Education & Experience
  • Master's degree in Statistics, Data Science, Computer Science, Economics, Mathematics, or a related quantitative field;
  • OR Bachelor's degree with 3+ years of relevant experience in model development or validation.
  • Prior experience developing and/or validating credit risk models is required.
  • 3+ years of experience in banking, financial services, or a related industry is preferred.

Technical Skills
  • Strong understanding of statistical modeling techniques, including regression and classification models.
  • Ability to evaluate model structure, assumptions, and validation methodologies.
  • Familiarity with machine learning models and their application in credit decisioning.
  • Proficiency in one or more programming languages/tools, such as SQL, Python, R, or SAS.
  • Working knowledge of credit policies and underwriting frameworks.
  • Familiarity with CECL models is a strong plus.

Professional Skills
  • Ability to work effectively across cross-functional teams, including Compliance, Audit, and Model Risk Management.
  • Strong analytical and critical thinking skills with attention to detail.
  • Effective written and verbal communication skills, including the ability to present technical concepts to non-technical audiences.
  • Strong organizational and prioritization skills in a fast-paced environment.

Additional Information
  • Experience working with regulatory, audit, or model risk management frameworks is a plus.
  • Proficiency in Microsoft Office Suite (Excel, Word, PowerPoint, Outlook) required.

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