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Quantitative Risk Management Jobs (NOW HIRING)

Expand Energy

Quantitative Risk Manager

Spring, TX · On-site

Job Summary We are seeking a Senior Quantitative Risk Manager to develop, enhance, and govern quantitative models used to value, risk assess, and explain exposures across natural gas, LNG, power, and ...

Expand Energy

Quantitative Risk Manager

Spring, TX

Job Summary We are seeking a Senior Quantitative Risk Manager to develop, enhance, and govern quantitative models used to value, risk assess, and explain exposures across natural gas, LNG, power, and ...

State Street Corporation

Quantitative Risk

Boston, MA · On-site

$104K - $180K/yr

The role has significant impact on the BAU risk management as well as the regulatory CCAR ... quantitative analysis, and implementation process; design and implement suitable and effective ...

WSFS Bank

Quantitative Risk Analyst

Philadelphia, PA · On-site

$64K - $105K/yr

Key Responsibilities: * Assist the Quantitative Risk Manager in constructing a Credit Decision Scorecards and statistically based credit risk modeling strategies based on quantitative modeling ...

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Quantitative Risk Management information

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$51.5K

$111.6K

$170K

How much do quantitative risk management jobs pay per year?

As of Jul 29, 2026, the average yearly pay for quantitative risk management in the United States is $111,556.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $129,000.00 per year, depending on experience, location, and employer.

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 skills, expertise in statistics or mathematics, and typically a degree in finance, economics, or a quantitative discipline. Familiarity with risk modeling software, programming languages like Python or R, and industry certifications such as FRM or CFA is often required. Outstanding problem-solving abilities, attention to detail, and effective communication set top professionals apart in this role. These skills are crucial for accurately assessing financial risks, making informed decisions, and communicating complex findings to stakeholders.

What is quantitative risk management?

Quantitative risk management is the process of using mathematical models, statistical techniques, and data analysis to identify, measure, and manage financial risks within an organization. Professionals in this field apply quantitative methods to assess potential losses from market movements, credit events, or operational failures, and help organizations make informed decisions to mitigate these risks. This approach is widely used in banking, insurance, asset management, and other financial sectors to ensure regulatory compliance and optimize risk-adjusted returns.

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

AspectQuantitative Risk ManagementQuantitative Analyst
Primary FocusAssessing and managing financial risksDeveloping models for investment strategies
CertificationsFRM, PRMCFA, CQF
Work EnvironmentFinancial institutions, risk departmentsInvestment banks, asset management firms
Key SkillsRisk modeling, regulatory knowledgeStatistical analysis, programming

Quantitative Risk Management focuses on identifying and mitigating financial risks within organizations, often requiring risk-specific certifications like FRM. In contrast, Quantitative Analysts develop models to support trading and investment decisions, emphasizing statistical and programming skills. Both roles are vital in finance but serve different strategic purposes.

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

Quantitative Risk Management professionals frequently work closely with departments such as trading, finance, and compliance. They provide analytical support by developing risk models and stress-testing scenarios, ensuring that trading strategies and investment decisions align with the institution's risk appetite. Regular communication with IT teams is also common, as these professionals often need to implement or improve risk measurement tools and data systems. This cross-functional collaboration is essential for maintaining a robust risk management framework and responding effectively to emerging risks.
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What cities are hiring for Quantitative Risk Management jobs? Cities with the most Quantitative Risk Management job openings:
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Quantitative Risk Management jobs near you
Infographic showing various Quantitative Risk Management job openings in the United States as of July 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 60% In-person, 20% Hybrid, and 20% Remote job distribution, with an average salary of $111,556 per year, or $53.6 per hour.

Quantitative Risk Management Consultant

Informatic Technologies

Chicago, IL • On-site

Other

Re-posted 9 days ago

Job description

The Quantitative Risk Team in the Risk Management Department is responsible for developing, analyzing, and back-testing models for clearing initiatives. Daily responsibilities include code release testing, historical data validation, margin and stress testing model validation, and portfolio back-testing. The candidate must have the ability to efficiently, effectively conduct research, analyze problems, formulate and implement solutions, and produce high quality results on time.

Candidates should also be willing to relocate to Chicago at their own costs.

Qualifications:

- Masters in Computer Science, Financial Engineering, Financial Mathematics, Mathematics, Physics, or a related discipline.

- Superb quantitative and analytical background.

- Excellent programming, communication, and documentation skills.

- Knowledge of financial markets.

- Work experience or education in advanced quantitative risk modeling and knowledge of statistical models in risk management preferred.

- Work experience or education in advanced derivatives modeling and knowledge of volatility models preferred.

- Work experience or education in curve construction and data validation preferred.

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