Engineering – Dallas Associate, Quantitative Engineering 033664

Job Duties:Associate Quantitative Engineering with Goldman Sachs & Co. LLC in Dallas Texas. 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. 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: Masters degree (U.S. or foreign equivalent) in Computer Science Financial Engineering 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 Bachelors degree (U.S. or foreign equivalent) in Computer Science Financial Engineering 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 Masters degree) OR two (2) years of experience (with a Bachelors 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.

The Goldman Sachs Group Inc. 2026. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race color religion sex national origin age veteran status disability or any other characteristic protected by applicable law.