Quantitative Engineering, Associate - Risk Engineering

The Goldman Sachs Group, Inc. is a leading global financial services firm providing investment banking, securities and investment management services to a substantial and diversified client base that includes corporations, financial institutions, governments and high-net-worth individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in London, Frankfurt, Tokyo, Hong Kong, Irving and other major financial centers around the world.

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.

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. RE has strong traditions of risk management, client service excellence and career development opportunities for our people.

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:

• Partnering with business units and broader Credit department to assess data availability, data sufficiency, and appropriate modelling approaches.
• Design and write data queries to extract credit data from credit systems and conduct analysis of portfolio profiles/performance, deep dive analysis of trends and summarize findings.
• Developing and monitoring the risk models and/or segmentation specific to the retail/securitization exposures.
• Quantification of the Basel risk and Stress-loss parameters utilizing the models/segmentation.
• Implement coding infrastructure and environment to facilitate analysis related to development and testing of models/scenarios.
• Documenting the model development/quantification procedures.
• Performing the ongoing Model/Segmentation validation tests assessing the strength/stability/accuracy of the models.
• Establishing requirements for data maintenance and management and working with Technology on implementation.

Qualifications:

• Strong quantitative and analytical skills with advanced degree (Masters preferred) in a quantitative discipline (Econometrics, Statistics, Mathematics, Financial Engineering etc.).
• Background with consumer risk models, risk segmentation systems and securitizations 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.