About Goldman Sachs

Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.

Goldman Sachs currently has 187 open roles on FindRole.

Listed pay typically runs $130,000–$250,000 across 60 roles with salary data.

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At a glance

TL;DR · Associate, Quantitative Engineering

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As an Associate in Quantitative Engineering at Goldman Sachs in New York, you will join a dynamic team focused on developing and refining economic and financial scenarios for various business units within the firm. Your day-to-day responsibilities include leveraging your expertise in financial markets, economics, statistical analysis, and programming to create sophisticated models that support decision-making processes across the organization. You will work with advanced technologies such as C++, Java, or Python to develop probability and pricing models using principles of stochastic calculus and no-arbitrage pricing theory. Additionally, you will contribute to risk management by creating quantitative risk analytics tools and performing scenario-based analysis, all while ensuring data integrity and scalability in your solutions. This role requires a strong background in Computer Science, Financial Engineering, Applied Mathematics, Data Science, Physics, or Operations Research, along with experience in statistical techniques like Bayesian analysis and machine learning algorithms.

Skills

Python C++ Java Bayesian analysis Time series analysis Machine learning algorithms Stochastic calculus No-arbitrage pricing theory Partial differential equations Multivariable calculus Linear algebra Numerical methods Optimization Probability Random processes Risk management Scenario-based analysis Factor models Data management tools

What you'll do

Develop and implement economic and financial scenarios for various business units.
Refine scenarios using knowledge in financial markets, economics, and statistical analysis.
Utilize programming skills to enhance scenario development processes.
Apply advanced quantitative techniques to develop probability and pricing models.
Conduct risk management analyses based on probabilistic and scenario-based methods.
Create data management tools for rigorous and scalable risk oversight support.
Perform performance analysis using statistical methods like linear regression.

What we're looking for

Master’s degree in a quantitative field and 1 year of experience or Bachelor’s degree and 2 years of experience in quantitative engineering.
Experience with C++, Java, or Python for developing financial models.
Proficiency in financial mathematics principles including stochastic calculus and no-arbitrage pricing theory.
Expertise in advanced econometric techniques such as Bayesian analysis and machine learning algorithms.
Capability to perform risk management and scenario-based analysis using statistical methods.
Development of quantitative risk analytics tools and rigorous data management systems.
Skills in statistics and performance analysis, including linear regression and time series analysis.