Goldman Sachs Risk-Dallas-Associate-Quantitative Engineering 

United States, Texas, Dallas 

393901143

RISK ENGINEERING

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.

Job Summary & Responsibilities

The Risk Economics Strats (RES) team is a central part of the Goldman Sachs risk management framework with primary responsibility for: 1) developing macroeconomic and financial scenarios for firm-wide scenario-based risk management; 2) developing and implementing statistical models for credit loss forecasting, business-as-usual risk management and regulatory stress testing requirements; and 3) analyzing large datasets of risk metrics to extract valuable insights about the firm’s exposures. To fulfill these objectives, Risk Economics Strats interface with a wide array of divisional, finance and risk management groups across the firm. The cross-disciplinary nature of the projects that RES engages in makes for a challenging and multifaceted work environment.

Responsibilities:

· Research and develop new statistical and econometric techniques for macroeconomic and financial scenarios.

· Implement coding infrastructure and environment to facilitate analysis related to development and testing of scenarios.

· Document macroeconomic models and methodologies for both internal and regulatory requirements.

· Provide overall support to the team to meet requirements for regulatory stress-testing and business-as-usual risk management.

· Collaborate with other teams to understand different use-cases in order to develop and refine projections for scenarios.

Qualifications:

· Strong quantitative and analytical skills with advanced degree (Masters or PhD) in a quantitative discipline (Econometrics, Statistics, Mathematics, Financial Engineering etc.).

· Background in economic theory/ econometric modelling and/or financial modeling is preferred.

· Ability to quickly learn and utilize quantitative modeling techniques.

· Strong coding skills preferably with a working knowledge of Python, Java or C++

· Excellent written and verbal communication skills.

· Strong project management and organizational skills and the ability to manage multiple assignments concurrently.