Job Description

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.

RISK ENGINEERING

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

In Credit Risk Strats, we are a team of quantitative modellers accountable for 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 quantitative/engineering 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:

• Design, 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, maintain, and test models using proprietary object database and programming language.
• Coordinate across multiple groups, including other teams of quantitative modellers, technology, and controllers to implement the new capital regulations.
• Communicate clearly complex modelling 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: 

• We consider candidates with all degree types in a quantitative discipline (Engineering, Mathematics, Physics, Statistics, Econometrics, Computer Science etc.).
• Excellent problem-solving, analytical thinking, and interpersonal skills.
• Strong programming skills and interest in model development/optimization/refactoring/debugging (C,C++, Python).
• Exceptional written and verbal communication skills – ability to explain complex modelling concepts to a non-technical audience.
• Ability to multi-task and managing deliverables across multiple stakeholders

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. 

We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. 

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

© The Goldman Sachs Group, Inc., 2023. All rights reserved.

Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity