Overview
On Site
Full Time
Skills
Data Analysis
Collaboration
Data Modeling
Investor Relations
International Relations
Information Retrieval
FX
Pricing
Modeling
Technical Writing
Performance Testing
Software Development
Requirements Elicitation
Testing
Documentation
Production Support
Computational Finance
Applied Mathematics
Data Science
Analytical Skill
Statistics
Performance Analysis
Linear Regression
Time Series
Portfolio Management
Finance
Mathematics
Linear Algebra
Numerical Analysis
Optimization
Probability
Risk Management
Management
Internal Auditing
Auditing
Data Management
Organizational Skills
Presentations
Leadership
Analytics
SAP BASIS
Law
Job Details
Job Description
Job Duties: Associate, Quantitative Engineering with Goldman Sachs Bank USA in Dallas, Texas. Perform historical data analysis to accurately model client behaviors, including liquidity outflows and funding optimizations. Collaborate with internal and external 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. Design proper portfolio management and hedging strategies against various market risks, including IR and FX risk. Build and challenge pricing models, identify and quantify vulnerabilities across market, credit, liquidity risk and modeling. Create and maintain clear and complete technical documentation of the model performance testing approach and process. Full software development lifecycle, including requirements gathering, design, coding, testing, documentation, deployment, and production support.
Job Requirements: Master's degree (U.S. or foreign equivalent) in Financial Engineering, Finance, Applied Mathematics, Data Science or related quantitative field and one (1) year of experience in job offered or a related quantitative engineering or analytical role OR Bachelor's degree (U.S. or foreign equivalent) in Financial Engineering, Finance, Applied Mathematics, Data Science or related quantitative field and two (2) years of experience in job offered or a related quantitative engineering or analytical role. Prior experience must include one (1) year of experience (with a Master's degree) OR two (2) years of experience (with a Bachelor's degree) with the following: utilizing Statistics and data driven performance analysis, including Linear Regression or Time Series analysis, for portfolio management; developing probability and scoring models as well as risk analytics utilizing financial mathematics principles, including linear algebra, numerical methods, optimization, and probability; performing risk management or scenario-based analysis and developing process maps for risk control self-assessment; managing quantitative and risk audit requirements and submissions and overseeing action plans as required by internal audit or Federal audit agencies; developing rigorous and scalable data management and analysis tools to provide risk oversight and support processes; creating quantitative proof of concepts, documenting risk and control frameworks, and organizing forums with internal and external stakeholders for new products and features launch; and presenting data-driven insights to senior leadership using analytics and visualizations.
The Goldman Sachs Group, Inc., 2025. 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.
Job Duties: Associate, Quantitative Engineering with Goldman Sachs Bank USA in Dallas, Texas. Perform historical data analysis to accurately model client behaviors, including liquidity outflows and funding optimizations. Collaborate with internal and external 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. Design proper portfolio management and hedging strategies against various market risks, including IR and FX risk. Build and challenge pricing models, identify and quantify vulnerabilities across market, credit, liquidity risk and modeling. Create and maintain clear and complete technical documentation of the model performance testing approach and process. Full software development lifecycle, including requirements gathering, design, coding, testing, documentation, deployment, and production support.
Job Requirements: Master's degree (U.S. or foreign equivalent) in Financial Engineering, Finance, Applied Mathematics, Data Science or related quantitative field and one (1) year of experience in job offered or a related quantitative engineering or analytical role OR Bachelor's degree (U.S. or foreign equivalent) in Financial Engineering, Finance, Applied Mathematics, Data Science or related quantitative field and two (2) years of experience in job offered or a related quantitative engineering or analytical role. Prior experience must include one (1) year of experience (with a Master's degree) OR two (2) years of experience (with a Bachelor's degree) with the following: utilizing Statistics and data driven performance analysis, including Linear Regression or Time Series analysis, for portfolio management; developing probability and scoring models as well as risk analytics utilizing financial mathematics principles, including linear algebra, numerical methods, optimization, and probability; performing risk management or scenario-based analysis and developing process maps for risk control self-assessment; managing quantitative and risk audit requirements and submissions and overseeing action plans as required by internal audit or Federal audit agencies; developing rigorous and scalable data management and analysis tools to provide risk oversight and support processes; creating quantitative proof of concepts, documenting risk and control frameworks, and organizing forums with internal and external stakeholders for new products and features launch; and presenting data-driven insights to senior leadership using analytics and visualizations.
The Goldman Sachs Group, Inc., 2025. 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.
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