Vice President, Quantitative Analyst

Responsibilities

• Design and implement quantitative analytics libraries and pricing models for structured credit instruments, delivering tools used directly by the trading business for valuation and risk management.
• Build pricing and valuation solutions using advanced numerical techniques, including Monte Carlo simulation and partial differential equation (PDE) solvers, to model complex financial instruments with precision.
• Apply a broad range of mathematical disciplines — including advanced calculus, mathematical finance, statistics, and probability — alongside hardware acceleration techniques to develop high-performance quantitative systems.
• Develop production-ready software using C++, C#, .NET, Java, Python, kdb+, and SQL, applying strong object-oriented design principles to deliver scalable and maintainable solutions.
• Integrate agentic AI and machine learning techniques into quantitative modeling, research workflows, and automation, adapting these approaches as technology and market conditions evolve.
• Collaborate with Traders, Structurers, and Technology teams to translate business requirements into robust analytical solutions that meet the demands of a live trading environment.
• Partner with Legal, Compliance, Market and Credit Risk, Audit, and Finance teams to ensure models and systems operate within a sound governance and control framework.

Required Qualifications & Skills

• Proficiency in numerical methods for financial modeling, specifically Monte Carlo simulation and PDE-based techniques applied to pricing and risk.
• Advanced programming ability in one or more of the following: C++, Python, Java, C#, or kdb+, with a strong foundation in object-oriented software design.
• Deep grounding in mathematical finance, probability theory, and statistical methods as applied to derivatives pricing and risk assessment.
• Ability to communicate complex quantitative concepts clearly to trading, structuring, and risk stakeholders, influencing decisions at a senior level.
• Sound judgment in assessing the risk and reward of transactions and business decisions, with a commitment to ethical conduct and regulatory compliance.

Beneficial Skills & Qualifications

• Demonstrated expertise in quantitative modeling for structured credit products, with hands-on experience across instruments such as CLOs, ABS, or synthetic securitizations.
• Familiarity with agentic AI frameworks or applied machine learning techniques in a quantitative finance or trading context.
• Experience with hardware acceleration methods for high-performance computing in financial applications.
• Working knowledge of kdb+ or SQL for time-series data management and analysis in a markets environment.
• Exposure to governance and control processes across functions such as Compliance, Credit Risk, or Audit within a regulated financial institution.