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Risk-NEW YORK-Vice President-Quantitative Engineering
Risk-NEW YORK-Vice President-Quantitative Engineering-May 2024
New York
May 29, 2026
ABOUT GOLDMAN SACHS
At Goldman Sachs, your skills and experiences will create a world of possibilities for our clients. From the latest IPO and market insights to investments in clean energy and infrastructure, each one
10,000+ employees
Financial Services
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About Risk-NEW YORK-Vice President-Quantitative 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, Bengaluru and other major financial centers around the world.

  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. The Risk Strats group in RE is a multidisciplinary group of quantitative experts focusing on risk and capital models. Within Risk Strats, Operational Risk Strats are responsible for designing, implementing and maintaining quantitative measures of operational risks, as well as metrics used to determine the firm's capital requirements.

  Responsibilities:

  Serve as a quantitative expert in Operational Risk. Communicate complex mathematical ideas with internal / external stakeholders such as risk managers, market making businesses, technology, senior management and regulators. Develop and refine models for operational risk stress test and capital, guided by mathematical/statistical and financial theories, empirical evidence and data, and regulatory capital requirements/specifications. Examples include Comprehensive Capital Analysis and Review (CCAR) and Dodd-Frank Act Stress Testing (DFAST). Develop and refine various risk factor driven quantitative operational risk measurements guided by mathematical/statistical and financial theories and empirical evidence and data. Implement models in production. This involves developing a comprehensive software code to execute the model in production environment, designing tests to ensure the accuracy of implementation as well as tests for the continuous functioning of the models. Provide comprehensive documentations of the models covering model purpose, model specification, testing description, empirical evidence, etc. Maintain and support model performance. This involves the calibrations of models on periodical basis, examination of test performances, adaption of the changes in operational risk dynamics to ensure appropriate model outcome. Address model limitations / uncertainties revealed by independent model review process. Provide informal supervision and quantitative / technical guidance to more junior risk management professionals, and take on leadership opportunities on department-wide initiatives

  In performing his / her job function an Operational Risk Strat will have the following opportunities:

  Broad exposure to and in-depth expertise in operational risk models. Exposure to challenging quantitative problems such as bottom-up modeling of various operational risks, Bayesian modeling of empirical data combined with scenario analysis, etc. Development of quantitative and programming skills as well as industry knowledge. Opportunities to work with other groups in various areas of the firm. Dynamic teamwork environment.

  Qualifications

  Advanced degree, such as Ph.D. in a quantitative field such as Engineering, Mathematics, Physics, Biology. Holders of M.SC. with relevant technical work experience will also be considered. Excellent command of mathematics, modeling and numerical algorithms. Deep knowledge of statistics and probability theory is highly desirable. Strong programming skills and experience. Proven ability to perform analysis and problem-solve using computational tools. Strong written and verbal communication skills. Self-motivated team player.

  Salary Range

  The expected base salary for this New York, New York, United States-based position is $150000-$250000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.

  Benefits

  Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. A summary of these offerings, which are generally available to active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here.

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