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Quantitative Risk Analyst Jobs in Utah (NOW HIRING)

Adobe

Sr. Manager Risk & Governance

Lehi, UT · On-site

Transform the security risk program with qualitative and quantitative insights, using AI, data analytics, and financial analysis. * Maintain and enhance Adobe's security risk framework, ensuring ...

Medallion Bank

Credit Risk Manager

Salt Lake City, UT · On-site

Minimum5years of experience in credit risk, financial analytics, or a related quantitative role within banking, fintech, or consumer finance. * Bachelor's degree in Finance, Economics, Statistics ...

Medallion Bank

Credit Risk Manager

Salt Lake City, UT · Hybrid

Minimum5years of experience in credit risk, financial analytics, or a related quantitative role within banking, fintech, or consumer finance. * Bachelor's degree in Finance, Economics, Statistics ...

Medallion Bank

Credit Risk Manager

Salt Lake City, UT · On-site

Minimum 5 years of experience in credit risk, financial analytics, or a related quantitative role within banking, fintech, or consumer finance. * Bachelor's degree in Finance, Economics, Statistics ...

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$51.4K

$121.9K

$218.5K

How much do quantitative risk analyst jobs pay per year?

As of May 28, 2026, the average yearly pay for quantitative risk analyst in Utah is $121,878.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $132,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Quantitative Risk Analyst, you need strong analytical and mathematical skills, experience with statistical modeling, and typically a degree in finance, mathematics, statistics, or a related field. Proficiency in programming languages such as Python, R, or MATLAB, and familiarity with risk management systems and financial databases are important technical requirements. Attention to detail, problem-solving abilities, and effective communication are vital soft skills for explaining complex analyses to stakeholders. These skills are crucial for accurately identifying, measuring, and mitigating financial risks in dynamic market environments.

What are some common challenges a Quantitative Risk Analyst faces when integrating new data sources into risk models?

Quantitative Risk Analysts often encounter challenges related to data quality, consistency, and compatibility when integrating new data sources into risk models. Ensuring that the data is accurate, timely, and relevant requires rigorous validation and sometimes complex data cleaning processes. Additionally, analysts must adapt existing risk models to accommodate new variables, which may involve re-calibrating parameters or even restructuring parts of the model. Effective collaboration with IT and data engineering teams is essential to streamline data integration and maintain model reliability.

What is a Quantitative Risk Analyst?

A Quantitative Risk Analyst is a professional who uses mathematical models, statistical techniques, and data analysis to assess and manage financial risks within an organization. They typically evaluate potential losses from market movements, credit defaults, or operational failures and help develop strategies to mitigate those risks. Their work is crucial in industries such as banking, investment, insurance, and asset management, where understanding and controlling risk is essential for financial stability and compliance. Quantitative Risk Analysts often work with complex financial instruments and large datasets, requiring strong analytical and programming skills.

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

AspectQuantitative Risk AnalystCredit Risk Analyst
Required CredentialsDegree in finance, economics, or mathematics; certifications like FRM or CFADegree in finance, economics, or related; certifications like FRM or CFA often preferred
Work EnvironmentFinancial institutions, investment firms, risk management departmentsBanks, lending institutions, credit agencies
Employer & Industry UsageUsed across finance sectors for risk modeling and analysisPrimarily in banking and lending for assessing creditworthiness
Comparison Search IntentUnderstanding differences in risk analysis rolesDistinguishing credit-specific risk roles from broader risk analysis

While both roles involve risk assessment and require similar credentials, a Quantitative Risk Analyst focuses on modeling and analyzing various financial risks using quantitative methods across multiple risk types. In contrast, a Credit Risk Analyst specializes in evaluating creditworthiness and managing credit risk specifically within lending and banking sectors.

What are the most commonly searched types of Quantitative Risk Analyst jobs in Utah? The most popular types of Quantitative Risk Analyst jobs in Utah are:
What are popular job titles related to Quantitative Risk Analyst jobs in Utah? For Quantitative Risk Analyst jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Quantitative Risk Analyst jobs in Utah look for? The top searched job categories for Quantitative Risk Analyst jobs in Utah are:
What cities in Utah are hiring for Quantitative Risk Analyst jobs? Cities in Utah with the most Quantitative Risk Analyst job openings:
Quantitative Risk Analyst jobs near you
Engineering-Salt Lake City-Associate, Quantitative Engineering-046336

Engineering-Salt Lake City-Associate, Quantitative Engineering-046336

Goldman Sachs, Inc.

Salt Lake City, UT

Other

Posted yesterday

Goldman Sachs rating

8.3

Company rating: 8.3 out of 10

Based on 25 frontline employees who took The Breakroom Quiz

29th of 141 rated banks

Job description

Job Duties: Associate, Quantitative Engineering with Goldman Sachs & Co. LLC in Salt Lake City, Utah. Multiple positions available. Develop, implement, and document scenarios comprised of a broad range of economic and financial variables for businesses within the Firm. Collaborate with internal stakeholders, analyzing user needs from a scenario design perspective and addressing data, model, and implementation issues. Analyze large data sets (structured and unstructured) to build predictive models of business-relevant market variables. Develop, refine, and improve scenarios by leveraging knowledge in financial markets, economics, current events, statistical analysis, and programming. Build and challenge risk models, identify and quantify vulnerabilities across market, credit, liquidity risk and modeling. Create and maintain clear and complete technical documentation of the risk-model performance testing approach and process.

Job Requirements: Master's degree (U.S. or foreign equivalent) in Computer Science/Engineering, Financial Engineering, Mathematical Finance, Applied Mathematics, Data Science, Operations Research or related quantitative field and one (1) year of experience in job offered or a related quantitative engineering role OR Bachelor's degree (U.S. or foreign equivalent) in Computer Science/Engineering, Financial Engineering, Mathematical Finance, Applied Mathematics, Data Science, Operations Research or related quantitative field and two (2) years of experience in job offered or a related quantitative engineering role. Prior experience must include one (1) year of experience (with a Master's degree) OR two (2) years of experience (with a Bachelor's degree) with 5 of the 7 following skills: C++, Java, or Python; developing probability and pricing models utilizing financial mathematics principles, including stochastic calculus, no-arbitrage pricing theory, partial differential equations, multivariable calculus, linear algebra, numerical methods, optimization, probability, or random processes; quantitative analysis and model development using advanced econometric, statistical, and mathematical techniques, including Bayesian analysis, time series analysis, or machine learning algorithms; performing risk management or scenario-based analysis; developing quantitative risk analytics, including factor models; developing rigorous and scalable data management and analysis tools to provide risk oversight and support the investment process; and statistics and data driven performance analysis, including Linear Regression or Time Series Analysis to measure performance. 

The Goldman Sachs Group, Inc., 2026. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran status, disability, or any other characteristic protected by applicable law.

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About Goldman Sachs

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At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869

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