Vice President Corporate Treasury

We are partnered with the Head of Corporate Treasury at a Tier One Investment Bank looking to expand their modeling team in New York. This is a multi-headcount team build out and they are seeking talented Quantitative Strategists to support a broad suite of analytics used across liquidity, balance‑sheet management, financial planning, and firm‑wide forecasting. The group operates at the intersection of front‑office trading, corporate treasury, and financial planning, working directly with large portfolios and P&L drivers. This is a highly technical environment suited for candidates who enjoy open‑ended quantitative problem solving, markets‑adjacent modeling, and end‑to‑end ownership of production models.

What You'll Do:

• Develop and enhance Treasury models, including:
• Net Interest Income (NII) forecasting
• Liquidity analytics and measurements
• P&L and risk explain frameworks
• Funds Transfer Pricing (FTP)
• Hedge accounting models
• Build quantitative components using practical methods such as PCA, Monte Carlo simulation, VaR/ES, stress scenario design, curve analytics, and risk‑factor decomposition.
• Own the full modeling lifecycle: implementation, testing, documentation, benchmarking, model governance, and production support.
• Work directly with Technology to productionize models, optimize performance, and maintain model infrastructure and data pipelines.
• Collaborate with Treasury, Finance, and Risk to translate business requirements into modeling solutions and communicate assumptions, behavior, and risk impacts to varied audiences.
• Lead complex initiatives, anticipate emerging risks across models or data, and help guide standards and best practices.
• Contribute to model improvements in areas such as curve engines, liquidity/margin modeling, LIBOR/ref‑rate transition impacts, and capital/stress frameworks.

What you'll bring:

• Advanced Degree in a quantitative discipline (Math, Physics, Statistics, Financial Engineering, etc)
• 4-6 years of experience in a similar discipline
• Strong programming ability in C++, Python, or Scala
• Experience related to:
• yield curve construction
• interest‑rate or macroeconomic fundamentals
• liquidity/margin/collateral concepts
• revenue, P&L, or balance‑sheet forecasting
• stress testing, PCA, Monte Carlo, VaR/ES, or risk‑factor modeling
• Strong communication skills and the ability to work cross functionally
• Strong problem solving skills and ability to work in a fast paced environment.