Engineering - New York - Vice President, Quantitative Engineering - 049539

Goldman Sachs • New York, NY

5d • $153,000 - $276,000 • Onsite

About The Position

Goldman Sachs & Co. LLC is seeking a Vice President, Quantitative Engineering in New York, NY. This role involves leading the development, implementation, and documentation of scenarios using a wide range of economic and financial variables for various business units within the Firm. The position requires collaboration with internal stakeholders to analyze user needs from a scenario design perspective and to resolve data, model, and implementation issues. A key responsibility is analyzing large datasets (both structured and unstructured) to construct predictive models for business-relevant market variables. The role also includes refining and enhancing scenarios by applying expertise in financial markets, economics, current events, statistical analysis, and programming. Additionally, the position involves building and challenging risk models, identifying and quantifying vulnerabilities across market, credit, and liquidity risk, and creating clear technical documentation for risk-model performance testing. The role also includes mentoring junior and mid-level team members.

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 the 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 the job offered or a related quantitative engineering role OR Doctorate (Ph.D.) 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 the job offered or a related quantitative engineering role.
• Prior experience must include three (3) years of experience (with Master’s degree) OR five (5) years of experience (with Bachelor’s degree) OR one (1) year of experience (with 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; developing pricing models for financial products to model risk, economics, and cash flows under normal and distressed market environments.

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager