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Model Validation Quant Jobs (NOW HIRING)

AIG

AI Model Validation Lead, GenAI

Atlanta, GA · On-site

$210K - $280K/yr

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

Live Oak Bank

Model Risk Analyst

Wilmington, NC · On-site

Model Validation & Effective Challenge: Conduct quantitative and qualitative validations of internally developed and vendor-provided models, assessing conceptual soundness, data, assumptions ...

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Model Validation Quant information

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How much do model validation quant jobs pay per hour?

As of Sep 13, 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 a model validation quant?

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 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 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.

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.

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Model Validation Quant jobs near you
Infographic showing various Model Validation Quant job openings in the United States as of September 2026, with employment types broken down into 2% As Needed, 83% Full Time, 13% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $108,152 per year, or $52 per hour.

Senior AI/ML Model Validation & Governance Specialist

New York, NY • On-site

Resourceful Talent Group
Recruiting and Staffing Services • 51 - 200 employees
Learn more about Resourceful Talent Groupexternal

$210K/yr

Full-time

Re-posted 23 days ago

Job description

We are seeking an experienced AI/ML Model Validation and Governance professional to join a highly established financial services organization in New York. This is a full-time hybrid opportunity based in New York City (3 days onsite per week) offering a base salary of up to $210,000, a 10% annual bonus, and a sign-on bonus.
This position will independently evaluate predictive, machine learning, Generative AI, and other advanced analytical models. The ideal candidate combines strong quantitative skills, hands-on Python and SQL experience, and a thorough understanding of model risk management within a regulated environment.
Key Responsibilities
  • Perform independent validation of predictive, statistical, AI/ML, and Generative AI models.
  • Evaluate model methodology, assumptions, data quality, implementation, performance, limitations, and intended use.
  • Conduct benchmarking, sensitivity analysis, stress testing, and performance testing.
  • Assess model explainability, bias, fairness, robustness, and regulatory compliance.
  • Review models using structured and unstructured data, including NLP, LLM, and RAG-based solutions.
  • Evaluate model monitoring frameworks, performance thresholds, and governance controls.
  • Document findings clearly and communicate recommendations to model developers, business stakeholders, risk teams, and senior management.
  • Support the continued development of AI governance and model risk standards.

  • Advanced degree in mathematics, statistics, computer science, data science, engineering, economics, or another quantitative discipline.
  • At least 4 years of direct experience in model validation, model risk management, or AI/ML governance.
  • Hands-on experience independently validating predictive or AI/ML models.
  • Strong Python and SQL skills.
  • Experience with benchmarking, explainability, bias and fairness testing, sensitivity analysis, and ongoing model monitoring.
  • Understanding of model risk management principles and regulatory expectations.
  • Experience working in financial services, insurance, banking, or another regulated industry.
  • Strong written and verbal communication skills.
  • Ability to work onsite in New York City three days per week.

Preferred Qualifications
  • Experience validating Generative AI, LLM, NLP, or RAG-based solutions.
  • Familiarity with AI governance and responsible AI frameworks.
  • Experience with structured and unstructured datasets.
  • Knowledge of SR 11-7 or comparable model risk management guidance.
  • Experience presenting validation findings to senior stakeholders or governance committees.

Apply