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Sr. Quantitative Risk Analyst

Geneva Trading
Sr. Quantitative Risk Analyst
Chicago, US
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Job Description

POSITION TITLE : Sr. Quantitative Risk Analyst

POSITION LOCATION : 190 S. LaSalle St., Suite 1800, Chicago, IL 60603


Monitor risk on a real-time basis, leveraging our monitoring and analysis framework to identify and communicate important risk-related information to traders and management. Model, analyze, and optimize risk tools, such as VaR and stress tests. Develop and implement analytical risk models to provide insight into the firm’s various trading activities. Interpret and utilize quantitative results from risk reporting efforts and communicate these effectively. Use sound judgment and decision-making ability to challenge assumptions and enforce risk limits. Work directly with traders and senior management on escalated risk issues. Engage with trading teams to understand and model their approach to risk. Perform risk and performance studies using SQL, Excel, and R/Python, often with extensive scripting and statistical analysis. Maintain an ongoing understanding of trends and concerns in the markets and how they relate to current positions and strategies. Develop and mentor junior members of the risk team. Telecommuting permitted up to 1 day per week.


This position requires a Master’s degree, or foreign equivalent, in Financial Mathematics, Computer Science, Statistics, Economics, or a related field, plus 4 years of experience in a quantitative risk analysis occupation or a related occupation. Additionally, the applicant must have professional experience with: 1) Evaluating and representing a market risk, including Historical Simulation, VaR, Scenario Analysis/Stress Testing, Greeks, or Option profiles; 2) Utilizing statistical methods including reading and replicating vendor white papers to perform various researches and projects; 3) Employing optimization libraries and statistical packages from R and Python; 4) Develop and cross-validate R and Python projects to facilitate research and analysis in different projects; 5) Manage code check-in and pull-requests to improve programming code-base; and 6) Fetch data from multiple databases including SQL and Bloomberg for analysis and research purpose.

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