New York, NY, USA
5 days ago
Global Commodities - Automated Trading Strategies - Analyst/Associate

The Automated Trading Strategies (ATS) group is responsible for systematic trading across FX, Rates, Commodities, and Credit markets. We design and implement cutting-edge proprietary quantitative models that drive our automated trading systems - including pricing, risk management and execution. This role offers career growth, exposure to a dynamic and collaborative environment, and the opportunity to drive revenue and expand our business.

Job Summary

As an Analyst or Associate in the Global Commodities ATS group, you will focus on commodities markets, including precious and base metals, energy, agriculture and index products. You will work closely with the trading desk to identify revenue opportunities and enhance our automated trading strategies. You'll be part of a team that values collaboration, innovation, and continuous learning, contributing to the firm's success and your professional growth.

Job Responsibilities 

Analyze large datasets to identify trading patterns and revenue opportunitiesConduct research to develop and improve quantitative models for trading strategiesBacktest and evaluate pricing, risk management, and execution algorithmsReview trading performance and contribute to data-driven decision makingMaintain and enhance trading software systems and analytical toolsSupport day-to-day trading operations

Required qualifications, capabilities and skills

Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, Engineering, or a related quantitative fieldProficiency in programming with C++, Java, or another object-oriented languageSolid understanding of statistics and data analysis techniquesAttention to detail, adaptability, and a collaborative mindsetDemonstrated interest in financial markets and systematic trading

Preferred qualifications, capabilities and skills

Prior work experience in commodities, quantitative trading, or a similar analytical roleFamiliarity with order types, L2 market data, and central limit order booksExperience with KDB+/q or similar time-series databases
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