Quantitative Modeller - Risk Engineering - Associate- Warsaw

RISK ENGINEERING

The Risk division is responsible for credit, market and operational risk, model risk, independent liquidity risk, and insurance throughout the firm.

Risk Engineering ("RE"), which is part of the Risk Division, is a central part of the Goldman Sachs risk management framework, with primary responsibility to provide robust metrics, data-driven insights, and effective technologies for risk management. RE is staffed globally with offices including Dallas, New Jersey, New York, Salt Lake City, London, Warsaw, Bengaluru, Singapore, and Tokyo.

In Credit Risk Strats, we are a team of quantitative modellers charged with managing the firm's capital and risk management models. The team is also responsible for designing, implementing and maintaining quantitative measures of risk used in Counterparty Credit Risk such as Expected Exposure (EE)  and Credit Valuation Adjustment (CVA) and also developing Stress Testing framework used to determine the firm's capital requirements. The position is ideal for collaborative individuals with a strong technical background and problem solving skills looking for a role in quantitative analysis and mathematical modelling.

RESPONSIBILITIES AND QUALIFICATIONS

The responsibilities of the quantitative modeller include:

• Develop, implement, and maintain quantitative measures used in the Counterparty Credit Risk area, such as Expected Exposure, Credit Valuation Adjustment, and Potential Exposure for risk management.
• Implement models in production using sophisticated software, and design tests to ensure the accuracy of implementation.
• Coordinate across multiple groups, including other teams of quantitative modellers, technology and controllers to implement the new capital regulations.
• Communicate clearly complex mathematical concepts with internal and external stakeholders such as risk managers, senior management and regulators.
• Perform quantitative analysis and facilitate understanding of the risk for a variety of financial derivatives across all asset classes, including exotic products.

Qualifications: 

• Quantitative skills with relevant degree (Bachelor's or Master's with relevant experience) in a quantitative discipline (Engineering, Mathematics, Physics, Statistics, Econometrics, Computer Science, Quantitative Finance etc.)
• Programming skills (Python, Java, C++, etc.)
• Problem solving skills and analytical thinking
• Written and verbal communication skills – ability to explain quantitative concepts to a non-technical audience