Associate, Quantitative Engineering with Goldman Sachs & Co. LLC in Salt Lake City, Utah. Multiple positions available. Develop, implement, and document scenarios comprised of a broad range of economic and financial variables for businesses within the Firm. Collaborate with internal stakeholders, analyzing user needs from a scenario design perspective and addressing data, model, and implementation issues. Requires: Master’s degree (U.S. or foreign equivalent) in Computer Science/Engineering, Financial Engineering, Mathematical Finance, Applied Mathematics, Data Science, Operations Research or related quantitative field and one (1) year of experience in job offered or a related quantitative engineering role OR Bachelor’s degree (U.S. or foreign equivalent) in Computer Science/Engineering, Financial Engineering, Mathematical Finance, Applied Mathematics, Data Science, Operations Research or related quantitative field and two (2) years of experience in job offered or a related quantitative engineering role. Prior experience must include one (1) year of experience (with a Master’s degree) OR two (2) years of experience (with a Bachelor’s degree) with 5 of the 7 following skills: C++, Java, or Python; developing probability and pricing models utilizing financial mathematics principles, including stochastic calculus, no-arbitrage pricing theory, partial differential equations, multivariable calculus, linear algebra, numerical methods, optimization, probability, or random processes; quantitative analysis and model development using advanced econometric, statistical, and mathematical techniques, including Bayesian analysis, time series analysis, or machine learning algorithms; performing risk management or scenario-based analysis; developing quantitative risk analytics, including factor models; developing rigorous and scalable data management and analysis tools to provide risk oversight and support the investment process; and statistics and data driven performance analysis, including Linear Regression or Time Series Analysis to measure performance.
Job Code: 046336
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