Risk Engineering, 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.  Risk Engineering is staffed globally with offices including Dallas, New Jersey, New York, Salt Lake City, London, Warsaw, Bengaluru, Singapore, and Tokyo.  As a member of Risk Engineering, you will interface with a variety of divisions around the firm as well as the other regional offices.  The interaction with numerous departments and the diverse projects that ensue allow for a challenging, varied, and multi-dimensional work environment.

Risk Engineering professionals are part of the value proposition of the firm and we balance our key functional responsibility of control with that of being commercial. Risk Engineering has strong traditions of risk management, client service excellence and career development opportunities for our people. 

We are seeking an Analyst/Associate level candidate to join the Prime Risk Strats team in Risk Engineering. The Prime Risk Strats is a new team, formally established in 2023, in Risk Engineering and focuses on building models and analytics for measuring and managing risk exposure to counterparties. Typical responsibilities and duties of the team and the role include the following:

Responsibilities 

• Developing risk models that use advanced mathematical/statistical approaches such as stochastic calculus, monte carlo simulations, machine learning.
• Implement risk models so that they can be run at scale reliably and efficiently.
• Perform detailed analysis of drivers of the model output and explain output using various visualization techniques.
• Analyze large datasets of risk metrics to extract valuable insights about counterparty risk.
• Present actionable insights to senior stakeholders for counterparty risk management.

Qualifications:

• Strong quantitative and analytical skills with a degree in a quantitative discipline (Statistics, Mathematics, Applied Mathematics, Engineering, etc.).
• Ability to quickly learn and utilize quantitative modeling techniques. 
• Strong writing, presentation, and communication skills
• Self-starter who can work with minimum guidance, ability to manage multiple priorities and work in a high-pressure environment.
• Familiarity with financial markets, financial assets and risk management practices is a plus
• Strong programming experience in at least one compiled or scripting language (e.g. C, C++, Java, Python)