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Entry Level Quantitative Risk Modeler Jobs (NOW HIRING)

Develop and maintain quantitative models for valuation, exposure measurement, and risk assessment across physical and financial natural gas, LNG, and power portfolios. * Build and enhance models for ...

Develop and maintain quantitative models for valuation, exposure measurement, and risk assessment across physical and financial natural gas, LNG, and power portfolios. * Build and enhance models for ...

Develop and maintain quantitative models for valuation, exposure measurement, and risk assessment across physical and financial natural gas, LNG, and power portfolios. * Build and enhance models for ...

Develop and maintain quantitative models for valuation, exposure measurement, and risk assessment across physical and financial natural gas, LNG, and power portfolios. * Build and enhance models for ...

Understanding of Market Risk Models * Ability to analyze and communicate quantitative risk ... implications * Preferred Requirements: * Advanced desktop technology skills such as Excel and ...

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Entry Level Quantitative Risk Modeler information

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$98K

$169.7K

$259.5K

How much do entry level quantitative risk modeler jobs pay per year?

As of Aug 8, 2026, the average yearly pay for entry level quantitative risk modeler in the United States is $169,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,500.00 and $199,000.00 per year, depending on experience, location, and employer.
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Infographic showing various Entry Level Quantitative Risk Modeler job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 8% Part Time, and 3% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $169,729 per year, or $81.6 per hour.

Quantitative Risk Management Consultant

Informatic Technologies

Chicago, IL • On-site

Other

Re-posted 18 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.