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Model Validation Manager Jobs (NOW HIRING)

AIG

AI Model Validation Lead, GenAI

Atlanta, GA

$210K - $280K/yr

AI Model Validation Lead Be part of something groundbreaking At AIG, we are making long-term ... We will incorporate best-in-class engineering and product management principles and your guidance ...

Guardianlife

Model Risk & Validation Lead

Bethlehem, PA · Hybrid

$103K - $169K/yr

Maintain and manage the model validation findings inventory, including issue severity assessment, remediation tracking, and validation closure support. * Support independent data risk assessments ...

Frost Bank

Model Validation Analyst II

San Antonio, TX · On-site

Evaluate governance for Model Risk Management by reviewing policies, controls, risk assessments, documentation standards, and validation standards that are required to manage modeling processes ...

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Model Validation Manager information

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$47.5K

$105.4K

$160.5K

How much do model validation manager jobs pay per year?

As of Jul 11, 2026, the average yearly pay for model validation manager in the United States is $105,415.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,500.00 and $132,000.00 per year, depending on experience, location, and employer.

How does a Model Validation Manager typically collaborate with other teams during the model validation process?

A Model Validation Manager works closely with model developers, risk management teams, and internal audit to ensure models meet regulatory and business standards. Collaboration often involves reviewing model documentation, discussing model assumptions and methodologies, and providing feedback for improvements. Effective cross-functional communication is essential, as validation managers must balance technical analysis with regulatory compliance and business objectives. Regular meetings and clear reporting lines help facilitate this collaboration, ensuring that model risks are identified and addressed promptly.

What is the difference between Model Validation Manager vs Quantitative Analyst?

AspectModel Validation ManagerQuantitative Analyst
CredentialsTypically requires advanced degrees in finance, mathematics, or statistics; certifications like CFA or FRM are commonOften holds degrees in finance, economics, or mathematics; certifications like CFA are also common
Work EnvironmentWorks in risk management, model validation teams within banks or financial institutionsWorks in trading, investment analysis, or risk departments within financial firms
Industry UsagePrimarily in banking, asset management, and financial services for model risk assessmentAcross investment firms, hedge funds, and banks for market analysis and trading strategies

The Model Validation Manager focuses on reviewing and validating financial models to ensure accuracy and compliance, often working within risk management teams. In contrast, a Quantitative Analyst develops and applies mathematical models for trading, investment, or risk purposes. While both roles require strong quantitative skills and similar credentials, their core responsibilities and work environments differ significantly.

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

To thrive as a Model Validation Manager, you need strong quantitative analysis skills, knowledge of risk management, and an advanced degree in mathematics, statistics, finance, or a related field. Familiarity with technical tools such as Python, R, SAS, and model risk management frameworks, as well as experience with regulatory compliance, is typically required. Exceptional problem-solving, communication, and stakeholder management abilities are important soft skills for this role. These skills ensure effective validation of financial models, regulatory compliance, and clear communication of complex findings to non-technical audiences.

What does a Model Validation Manager do?

A Model Validation Manager is responsible for overseeing the validation of financial, risk, or predictive models within an organization. Their primary duties include ensuring that models are accurate, reliable, and compliant with regulatory requirements. They lead teams that assess model performance, identify potential weaknesses, and recommend improvements. This role helps maintain the integrity of models used in decision-making processes, particularly in industries like banking and finance.
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Model Validation Manager jobs near you
Infographic showing various Model Validation Manager job openings in the United States as of July 2026, with employment types broken down into 85% Full Time, 13% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution, with an average salary of $105,415 per year, or $50.7 per hour.
Model Validation Analyst

Model Validation Analyst

First Electronic Bank

Salt Lake City, UT • On-site

Full-time

Posted 19 days ago

Job description

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.