Job Duties: Vice President, Quantitative Engineering with Goldman Sachs & Co. LLC in Dallas, Texas. Multiple positions available. Lead the development, implementation, and documentation of 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. Mentor junior and mid-level team members.
Job Requirements: Master’s degree (U.S. or foreign equivalent) in Computer Science, Financial Engineering, Applied Mathematics, Data Science, Operations Research, or related quantitative field and three (3) years of experience in job offered or a related quantitative engineering role OR Bachelor’s degree (U.S. or foreign equivalent) in Computer Science, Financial Engineering, Applied Mathematics, Data Science, Operations Research, or related quantitative field and five (5) years of experience in job offered or a related quantitative engineering role OR PhD 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. Prior experience must include three (3) years of experience (with a Master’s degree) OR five (5) years of experience (with a Bachelor’s degree) OR one (1) year of experience (with a PhD degree) with 5 of the 8 following skills: C++, Java, or Python; performing financial mathematics, including at least one of the following: stochastic calculus, no-arbitrage pricing theory, multivariable calculus, linear algebra, probability theory, numerical methods, or Monte-Carlo techniques; performing analysis leveraging market risk, credit risk, liquidity risk, or mathematical finance concepts; object-oriented programming and scripting programming languages such as Python or Java; implementing mathematical models or analytics in production-quality software; working with database query languages, such as SQL, MongoDB, or other data management tools to process large datasets; applying algorithms or data structures to write complex programs; and developing pricing models for financial products to model risk, economics, and cash flows under normal and distressed market environments.
©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.
Skills Required
- Master's in Computer Science, Financial Engineering, Applied Mathematics, Data Science, Operations Research, or related + 3 years experience OR Bachelor's + 5 years OR PhD + 1 year
- Proficiency in C++, Java, or Python
- Experience performing financial mathematics (e.g., stochastic calculus, no-arbitrage pricing, multivariable calculus, linear algebra, probability, numerical methods, Monte-Carlo)
- Experience with market risk, credit risk, liquidity risk, or other mathematical finance concepts
- Object-oriented programming and scripting (e.g., Python or Java)
- Implementing mathematical models or analytics in production-quality software
- Working with database/query languages and data management tools (e.g., SQL, MongoDB) to process large datasets
- Applying algorithms and data structures to write complex programs
- Developing pricing models for financial products to model risk, economics, and cash flows under normal and distressed markets
- Ability to analyze large structured and unstructured datasets to build predictive models
- Mentoring and leading junior and mid-level team members
Goldman Sachs Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Goldman Sachs and has not been reviewed or approved by Goldman Sachs.
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Healthcare Strength — Coverage includes medical, dental, vision, disability, life and accident insurance, with multiple plan options and most premiums subsidized; coverage often starts on day one. Wellness resources, on-site health centers in some locations, and EAP access reinforce the depth of health support.
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Parental & Family Support — Family care includes on-site childcare in some offices, expectant parent resources, and transitional programs for returning parents. Feedback suggests parental leave is very generous, with reports of around 20 weeks paid leave and stipends for adoption, surrogacy, and fertility-related services.
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Retirement Support — The firm provides a 401(k) plan with employer matching contributions and broad financial education to help employees plan for retirement. Resources also support saving for education and preparing for unexpected events.
Goldman Sachs Insights
What We Do
At Goldman Sachs, we believe progress is everyone’s business. That’s why we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, Goldman Sachs is a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices in all major financial centers around the world. More about our company can be found at www.goldmansachs.com
