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Associate Quantitative Risk Analyst Jobs in Utah

UnitedHealth Group

Credit Risk Analyst

Draper, UT · On-site +1

This role supports the broader risk governance frameworks, regulatory compliance, and strategic decision-making through quantitative analysis and reporting. The Risk Management function is dedicated ...

UnitedHealth Group

Credit Risk Analyst

Draper, UT · On-site

This role supports the broader risk governance frameworks, regulatory compliance, and strategic decision-making through quantitative analysis and reporting. The Risk Management function is dedicated ...

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Associate Quantitative Risk Analyst information

What does a quantitative risk analyst do?

A quantitative risk analyst evaluates financial risks using mathematical models and statistical techniques to identify potential losses and inform decision-making. They analyze data, develop risk assessment tools, and often use software like Excel, R, or Python to support risk management strategies. Strong analytical skills and knowledge of finance and statistics are essential for this role.

What are some common challenges faced by Associate Quantitative Risk Analysts in their first year, and how can they overcome them?

In their first year, Associate Quantitative Risk Analysts often encounter challenges such as adapting to complex financial models, learning to interpret large datasets, and effectively communicating technical findings to non-technical stakeholders. Navigating regulatory requirements and understanding the company's risk management framework can also be demanding. To overcome these obstacles, new analysts should proactively seek mentorship, participate in team discussions, and leverage internal training resources to build both technical and soft skills. Regular collaboration with colleagues in risk, finance, and IT departments can also provide valuable insights and accelerate professional growth.

Is a quant analyst a high paying job?

A quantitative risk analyst typically earns a competitive salary, especially in finance and investment firms, with compensation often increasing with experience, advanced degrees, and specialized skills in programming and statistical analysis. While salaries vary by location and employer, the role is generally considered well-paying within the finance industry.

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

AspectAssociate Quantitative Risk AnalystCredit Risk Analyst
Required CredentialsBachelor's in finance, economics, or related field; often some familiarity with quantitative methodsBachelor's in finance, economics, or related field; certifications like CFA or FRM are common
Work EnvironmentFinancial institutions, risk management teams, quantitative departmentsBanking, lending institutions, credit departments
Employer & Industry UsageUsed in risk modeling, data analysis, and quantitative assessmentsFocuses on assessing creditworthiness and loan risk

The Associate Quantitative Risk Analyst primarily focuses on developing models and analyzing data to measure financial risks, often working with quantitative tools. In contrast, a Credit Risk Analyst concentrates on evaluating the creditworthiness of borrowers and managing credit risk. While both roles require similar educational backgrounds and work within financial institutions, their core responsibilities differ—one emphasizes quantitative modeling, the other credit assessment.

How much does a quant risk analyst make?

The average salary for a quantitative risk analyst at Morgan Stanley is typically between $80,000 and $150,000 annually, depending on experience, location, and level of seniority. Entry-level positions may start lower, while experienced analysts with advanced skills in programming and risk modeling can earn higher compensation, often supplemented with bonuses and benefits.

What is the salary of a quant risk analyst?

The salary of a quantitative risk analyst typically ranges from $70,000 to $150,000 annually, depending on experience, location, and the complexity of the role. Entry-level positions may start lower, while experienced analysts with advanced skills in programming and risk modeling can earn higher compensation, often supplemented with bonuses and benefits.

What are Associate Quantitative Risk Analysts?

Associate Quantitative Risk Analysts are entry- to mid-level professionals who help financial institutions and organizations assess and manage risk using mathematical models and statistical techniques. They analyze data to identify potential risks, develop risk management strategies, and support decision-making processes. Their work often involves using quantitative software, working with large datasets, and collaborating with other risk management and finance professionals. Typically, they have backgrounds in mathematics, statistics, finance, or related fields.

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

To thrive as an Associate Quantitative Risk Analyst, you need a strong background in mathematics, statistics, finance, and data analysis, typically supported by a relevant degree such as in finance, mathematics, or economics. Familiarity with statistical software (like R, SAS, or Python), financial modeling tools, and possibly certifications such as FRM or CFA is highly valuable. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting complex data and presenting findings. These competencies are essential for accurately assessing financial risks and supporting informed decision-making in risk management environments.
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Associate Quantitative Risk Analyst jobs near you
Engineering-Salt Lake City-Associate, Quantitative

Engineering-Salt Lake City-Associate, Quantitative

The Goldman Sachs Group

Salt Lake City, UT

Other

Posted 17 days ago

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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