Markets Treasury – Liquidity and Capital Optimization – Vice President

Overview

In this role you will lead optimization efforts for the Markets Treasury team, improving the use of financial resources across balance sheet, liquidity, leverage, and capital. You’ll work with cross-functional partners to surface opportunities, implement optimization strategies, and drive measurable improvements within a regulated environment. The role combines quantitative methods, collaboration with trading desks, and technology-enabled analytics to scale solutions. This is a high-impact opportunity to help shape the firm’s liquidity and risk strategy at scale.

Responsibilities

• Develop and implement optimization strategies to address binding financial resource constraints
• Lead optimization efforts across collateral, liquidity (LCR/NSFR/internal stress models), counterparty credit risk RWA, market risk RWA, leverage, and GSIB
• Analyze drivers of financial resource consumption at firm and legal-entity levels
• Collaborate with FICC & Equities desks to optimize collateral usage for liquidity value
• Develop optimizers, data-mining approaches, benefit trackers, and analytics; leverage AI tooling to scale solutions
• Maintain and improve internal liquidity methodologies and advocate for methodological changes
• Review counterparty portfolios and trade structures to identify optimization opportunities
• Engage with third-party vendors and clearing houses to align internal and external roadmaps
• Monitor competitive landscape and regulatory constraints across regions

Key requirements

• Bachelor’s degree in a quantitative field
• Extensive experience in structured financing, financing, XVA, or financial resource optimization
• Experience structuring derivative and securities financing trades
• Knowledge of US liquidity topics (LCR/NSFR, Basel III, GSIB, SLR, SCB, initial margin)
• Strong pricing and risk management knowledge for securities financing and derivatives (cross-asset, XVAs)
• Proven ability to work with large data sets across multiple tech stacks
• Track record partnering with technology and quantitative research teams

• collaboration
• communication
• problem-solving
• Python
• SQL
• Tableau

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