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Job Duties: Associate, Quantitative Engineering with Goldman Sachs & Co. LLC in New York, New York. 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. Analyze large data sets (structured and unstructured) to build predictive models of business-relevant market variables. Develop, refine, and improve scenarios by leveraging knowledge in financial markets, economics, current events, statistical analysis, and programming. Build and challenge risk models, identify and quantify vulnerabilities across market, credit, liquidity risk and modeling. Create and maintain clear and complete technical documentation of the risk-model performance testing approach and process.Job Requirements: Master’s degree (U.S. or foreign equivalent) in Mathematics, Mathematics of Finance, Computer Science, Financial Engineering, Applied Mathematics, or a related quantitative field and one (1) year of experience in the job offered or a related quantitative engineering role OR Bachelor’s degree (U.S. or foreign equivalent) in Mathematics, Mathematics of Finance, Computer Science, Financial Engineering, Applied Mathematics, or a related quantitative field and three (3) years of experience in the job offered or a related quantitative engineering role. Prior employment must include one (1) year of experience (with a Master’s degree) OR three (3) years of experience (with a Bachelor’s degree) with: 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: 8077192Salary Range: The expected annual base salary for this New York, New York, United States-based position is $150,000. 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: https://www.goldmansachs.com/careers/discover/benefits-summary-US.pdf

Minimum Salary: 150,000 Maximum Salary: 150,000 Salary Unit: Yearly