Commodities Quantitative Analyst (AVP)

About the Role

Citi's Markets Quantitative Analytics (MQA) team develops and supports sophisticated models and analytics for the Markets business. The team leverages diverse modeling and pricing techniques to analyze complex dynamics in commodities markets, developing cutting-edge solutions to facilitate business growth. We are seeking a highly motivated Quantitative Analyst to join our front office Commodities Quant team in Houston. This role offers an opportunity to contribute directly to the development of advanced quantitative models and analytics that drive trading strategies and risk management frameworks. As an AVP, you will solve complex financial problems using sophisticated mathematical and computational methods in a fast-paced and intellectually stimulating environment.

Key Responsibilities

• Develop and enhance analytics libraries for pricing and risk management of commodity derivatives.
• Design, implement, and rigorously test quantitative models for the trading business, utilizing mathematical and computer science techniques.
• Collaborate closely with Traders, Sales, and Structurers to understand business requirements and deliver tailored quantitative solutions.
• Work proactively with control functions such as Model Risk Management, Legal, Compliance, Market and Credit Risk, and Audit to ensure robust governance and control.
• Drive responsible financial practices, foster good governance, and uphold ethical standards.
• Adhere strictly to all internal policies and procedures and ensure full compliance with regulatory requirements.

Requirements & Tech Stack

• Experience in a quantitative modeling or analytics role, with preference for the financial sector.
• Solid understanding of commodities markets is highly desirable, but not mandatory with strong foundational quantitative skills.
• Expertise in programming, particularly C++ and Python, with proven experience in developing robust quantitative libraries and applications.
• Strong theoretical and practical background in market data, statistics, and probability, including application to risk assessment in complex financial instruments.
• Demonstrated ability to solve analytical equations and design numerical schemes for analyzing intricate financial contracts.
• Proficiency in software design principles and best practices for developing high-quality, maintainable code.
• Exceptional clear and concise written and verbal communication skills to articulate complex technical concepts.
• An advanced degree (Master's or PhD) in a quantitative field such as Financial Engineering, Mathematics, Physics, Computer Science, or a related discipline.