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Quantitative Risk Analyst Jobs in Illinois (NOW HIRING)

William Blair

Risk Analyst

Chicago, IL · Hybrid

Utilize enterprise risk management principles and methodologies to perform quantitative analysis such as risk grading, financial risk, rate of failure. * Collaborate with business partners to ...

SageSure

Catastrophe Risk Analyst

Chicago, IL · On-site

Ability to explain complex scientific or quantitative findings to non-technical audiences. * Strong team player with a collaborative mindset and attention to detail Highly preferred candidates also ...

William Blair

Risk Analyst

Chicago, IL · On-site

$77K - $95K/yr

Utilize enterprise risk management principles and methodologies to perform quantitative analysis such as risk grading, financial risk, rate of failure. * Collaborate with business partners to ...

Alliant

Senior Credit Risk Analyst

Chicago, IL · On-site

$84K - $131K/yr

... analytical frameworks for loan origination and loss forecasting ... Review relevant data to identify the quantitative and qualitative factors driving the credit risk ...

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Quantitative Risk Analyst information

See Illinois salary details

$54.8K

$129.7K

$232.6K

How much do quantitative risk analyst jobs pay per year?

As of Jun 23, 2026, the average yearly pay for quantitative risk analyst in Illinois is $129,730.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,000.00 and $141,000.00 per year, depending on experience, location, and employer.

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 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 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 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 are the most commonly searched types of Quantitative Risk Analyst jobs in Illinois? The most popular types of Quantitative Risk Analyst jobs in Illinois are:
What are popular job titles related to Quantitative Risk Analyst jobs in Illinois? For Quantitative Risk Analyst jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Quantitative Risk Analyst jobs in Illinois look for? The top searched job categories for Quantitative Risk Analyst jobs in Illinois are:
Quantitative Risk Analyst jobs near you
Infographic showing various Quantitative Risk Analyst job openings in Illinois as of June 2026, with employment types broken down into 4% As Needed, 81% Full Time, 8% Part Time, 2% Temporary, 4% Contract, and 1% Nights. Highlights an 83% Physical, 7% Hybrid, and 10% Remote job distribution, with an average salary of $129,730 per year, or $62.4 per hour.
Quantitative Risk Analyst

Quantitative Risk Analyst

Informatic Technologies, Inc.

Chicago, IL • On-site

Other

Posted 22 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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