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How much do quantitative risk manager jobs pay per year?

As of Jul 9, 2026, the average yearly pay for quantitative risk manager in Utah is $101,557.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,900.00 and $117,400.00 per year, depending on experience, location, and employer.

What can I do with a quantitative risk management degree?

A degree in quantitative risk management prepares individuals for roles such as risk analyst, risk manager, or quantitative analyst in finance, insurance, or consulting firms. These roles involve assessing and modeling financial risks using statistical tools, programming languages like Python or R, and risk management frameworks. Professionals in this field often work with regulatory compliance and may pursue certifications like FRM or PRM.

What is the salary of a quant risk manager?

A quantitative risk manager's salary typically ranges from $100,000 to $200,000 annually, with higher compensation often associated with experience, advanced degrees, and certifications such as FRM or CFA. In addition to base salary, bonuses and performance incentives can significantly increase total compensation in this role.

What does a quantitative risk manager do?

A quantitative risk manager analyzes financial data and models to identify, measure, and manage risks within an organization. They use statistical techniques, programming skills, and risk management tools to develop strategies that minimize potential losses and ensure regulatory compliance.

How does a Quantitative Risk Manager typically collaborate with other departments within a financial institution?

Quantitative Risk Managers work closely with teams such as trading, compliance, IT, and senior management to identify, measure, and mitigate financial risks. They often translate complex quantitative models into actionable insights for non-technical stakeholders and facilitate the integration of risk metrics into daily decision-making processes. Collaboration is essential for ensuring that risk assessments align with business objectives and regulatory requirements, often requiring regular cross-functional meetings and clear communication.

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

To thrive as a Quantitative Risk Manager, you need strong analytical abilities, a deep understanding of statistics and financial mathematics, and typically an advanced degree in finance, mathematics, or a related field. Proficiency in programming languages like Python or R, experience with risk modeling software, and certifications such as FRM or CFA are highly valuable. Exceptional problem-solving, communication, and collaboration skills help you convey complex risk metrics to stakeholders and work effectively in cross-functional teams. These skills ensure accurate risk assessments, regulatory compliance, and informed decision-making in dynamic financial environments.

How much do quant risk managers make?

Quantitative risk managers typically earn between $100,000 and $200,000 annually, with senior roles and those in major financial centers earning higher salaries. Compensation often includes bonuses and benefits, and strong skills in mathematics, programming, and risk modeling are essential for higher-paying positions.

What is a Quantitative Risk Manager?

A Quantitative Risk Manager is a professional who uses mathematical models, statistical analysis, and quantitative techniques to identify, measure, and manage financial risks within an organization. They often work in banks, investment firms, or insurance companies to analyze market, credit, and operational risks. Their responsibilities include developing risk models, monitoring risk exposures, and advising senior management on risk mitigation strategies. They play a key role in ensuring that organizations make informed decisions and comply with regulatory requirements.

What is the difference between Quantitative Risk Manager vs Quantitative Analyst?

AspectQuantitative Risk ManagerQuantitative Analyst
Primary FocusAssessing and managing risk exposure across financial portfoliosDeveloping models and algorithms for investment strategies
Required CredentialsAdvanced degrees in finance, mathematics, or related fields; certifications like FRM or CFADegrees in finance, mathematics, or statistics; often pursuing CFA or similar
Work EnvironmentFinancial institutions, risk management departmentsInvestment firms, hedge funds, banks
Key SkillsRisk assessment, regulatory knowledge, quantitative modelingData analysis, programming, financial modeling

While both roles involve quantitative skills and financial knowledge, Quantitative Risk Managers focus on identifying and mitigating risks within organizations, whereas Quantitative Analysts primarily develop models to inform investment decisions. Understanding these differences helps professionals choose the right career path or job search focus.

What are popular job titles related to Quantitative Risk Manager jobs in Utah? For Quantitative Risk Manager jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Quantitative Risk Manager jobs in Utah look for? The top searched job categories for Quantitative Risk Manager jobs in Utah are:
What cities in Utah are hiring for Quantitative Risk Manager jobs? Cities in Utah with the most Quantitative Risk Manager job openings:
Quantitative Risk Manager jobs near you
Model Validation Analyst

Model Validation Analyst

First Electronic Bank

Salt Lake City, UT

Other

Re-posted 17 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.

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