Quantitative Engineering, Risk Economics Strats, Vice President, Salt Lake City

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 Salt Lake City, Dallas, New Jersey, New York, 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.

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

Responsibilities

• Partner with business units and broader Credit department to assess appropriate modelling approaches as well as data availability / sufficiency.
• Design and write data queries to extract data from credit systems and conduct analysis of portfolio performance, deep dive analysis of trends, summarize findings and recommend changes.
• Design, build, and enhance risk models specific to the credit exposures, and document the model development / quantification procedures.
• Perform ongoing model monitoring assessing the strength / stability / accuracy of the models.
• Establish requirements for data maintenance and management and work with Technology on implementation.
• Provide support for portfolio credit risk loss forecast and governance by tracking the actual performance to expectations.
• Create Management Loss Forecast reporting using Tableau or other cutting-edge visual interface-based tools to monitor portfolio performance at portfolio segment level (e.g., product, vintage, risk segment, score band, or marketing channel).
• Develop analytical reports and presentations for senior management, executive committees and regulatory exams.

Qualifications :

ABOUT GOLDMAN SACHS

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