Risk-Bengaluru-Analyst-Quantitative Engineering

4 weeks ago

Bengaluru, India Goldman Sachs Full time

Risk Engineering is part of the Risk Division of Goldman Sachs. This is a central part of the Goldman Sachs risk management framework, with primary responsibility to provide analytical solutions, data-driven insights, robust metrics and effective technologies for risk management. RE is staffed globally with offices in USA, UK, Europe, Bengaluru, Singapore, and Tokyo. 

GSRisk group in Risk Engineering is a multidisciplinary group of quantitative experts responsible for building the next generation of Risk pricing and analytics platform. The team builds and deploys advanced pricing and analytics platforms that deliver sophisticated risk measures like Value at Risk (VaR) and Stress Tests, driving significant efficiencies and ensuring best-in-class risk management.

The responsibilities of GSRisk Strats include:

Design, implement, and maintain the risk platform that scales to billions of scenarios across risk stripes, financial products, asset classes and metrics Design declarative domain specific languages to express risk models across risk stripes and asset classes Perform quantitative analysis on large datasets to facilitate understanding of the market risk for a variety of financial derivatives, including exotic products Liaise with multiple groups across the firm including strats, traders, technology, controllers, and treasury to converge on a shared risk platform Communicate clearly about complex mathematical concepts with internal and external stakeholders such as risk managers, market making businesses, senior management and regulators. Mentor and develop junior risk management professionals withing the division

In performing the job function, an associate in GSRisk Strats will have the following opportunities:

Exposure to challenging problems at the intersection of mathematics, computer science, and finance Exposure to challenging quantitative problems such as derivative pricing, modeling market and counterparty risk for complex portfolios, large scale Monte Carlo simulations of portfolios across the firm, and fast approximation of market risk measurements Exposure to challenging system design problems such drawing risk insights from billions of prices Development of quantitative, programming and system design skills, as well as product and market knowledge. Work in a dynamic teamwork environment.

Basic Qualifications:

Bachelor's Degree in a relevant field: Computer Science, Mathematics, Physics, Engineering Strong quantitative, programming, and system design skills  Good knowledge of statistics, system design, econometric modeling and probability theory. Strong written and verbal communication skills – ability to explain complex quantitative concepts to a non-technical audience.

Preferred Qualifications:

Competence in advanced mathematics, system design, and data science Experience working with large data sets

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