VP - Commodity Quantitative Strategist
VP Commodity Quantitative Strategist
New York City
Role Overview
A leading global investment bank is seeking a VP Commodity Quantitative Strategist to join their commodities trading desk and closely support traders, structurers, and risk. The role focuses on the design, implementation, and ownership of quantitative models, analytics, and trading tools used for pricing, risk management, and market‑making across commodity markets. This is a true front‑office role with direct exposure to trading decisions and P&L.
Key Responsibilities
- Design, implement, and maintain pricing and risk models for commodity products, including vanilla and non‑linear products
- Develop front‑office analytics and trading tools for pricing, hedging, scenario analysis, and P&L attribution
- Partner closely with traders and structurers to translate market views and trading strategies into robust quantitative solutions
- Improve model performance, numerical stability, and computational efficiency for real‑time trading use
- Own models through their full lifecycle: research, calibration, implementation, validation support, and production deployment
- Provide quantitative support during market events, stress scenarios, and new product launches
Required Qualifications
- Advanced degree (MSc or PhD) in Mathematics, Physics, Engineering, Quantitative Finance, or a related field
- 2+ years of experience in a front‑office quant or strat role at an investment bank, trading firm, or commodity trading business
- Strong understanding of derivatives pricing, stochastic processes, and numerical methods
- Solid programming skills in C++ and/or Python, with production grade standards
- Ability to work effectively with traders in a fast pace front office environment
Preferred Qualifications
- Experience in energy markets (oil, natural gas, power) is preferred but not required
- Familiarity with commodity volatility modeling and curve calibration
- Experience with Monte Carlo and/or PDE methods
- Strong communication skills and ability to explain complex quantitative concepts to non‑quants
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