Job Description

Corporate Treasury (CT) lies at the heart of Goldman Sachs, ensuring all the businesses have the appropriate level of funding to conduct their activities, while also optimizing the firm’s liquidity and managing its risk. 

The mission statement of the Resource Allocation (RA) Strats team within CT is to develop quantitative frameworks to source and optimize the Firm’s liabilities within risk, market and operating limits. We partner with senior leadership across the firm to manage and execute the firm’s central liabilities across unsecure, secured and deposit channels; set appropriate incentives for assets and liabilities businesses; and create funding plans for budget and stress.

RA’s primary objectives are:

• Optimize the firm’s liability stack across diverse channels, products, tenors
• Create benchmarks to track execution of central liabilities
• Quantify complex relationships of a dynamic balance sheet across multiple dimensions such as earnings, risk, incentives, and regulatory constraints
• Set appropriate incentives for assets and liabilities businesses

Responsibilities:

• Develop quantitative frameworks and mathematical models to optimize the firm’s liabilities
• Understand business needs, data requirements and specifications; facilitate and develop process workflow required to support implementation of data engineering solutions
• Understand and model all the regulatory constraints impacting the Firm’s balance sheet: liquidity, leverage, capital, market limits
• Develop analytics to inform BAU unsecured funding, execution and limits management
• Analyze model output and facilitate understanding of model results by non-technical clients
• Manage/Execute end-to-end systems development cycle from requirements analysis, coding, testing, UAT and post go live maintenance

Basic Qualifications

• Advanced degrees (PhD or Masters) in quantitative field such as Engineering. Computer Science, Mathematics, Physics -- or bachelor’s with relevant work experience
• 5+ years of relevant experience
• Strong analytical and problem-solving ability
• Python or similar programming language
• Excellent communication skills, including experience speaking to both technical and business audiences and working globally across multiple regions
• Familiarity with financial markets, financial products, and optimization is a plus
• Self-motivated team player

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