At J.P. Morgan, we are a leading liquidity provider in global macro markets, offering a comprehensive range of products. As part of our Automated Trading Strategies (ATS) team, you will have the opportunity to work on the trading floor in Singapore, focusing on commodities markets. This role offers career growth and the chance to collaborate with a dynamic team to drive revenue and expand our business.

As an Associate in the Automated Trading Strategies team, you will be at the forefront of systematic trading in commodities markets, including Precious and Base metals, Energy, Agricultural, and Indices products. You will work closely with the trading desk to identify revenue opportunities and enhance our trading strategies. Your role will be pivotal in maintaining and improving our trading software systems and tools, contributing to the success of our team and the firm.

Job Responsibilities:

Analyze data to identify patterns and revenue opportunities Conduct research to develop models and methods for trading problems Back test and assess pricing, risk management, and execution strategies Review trading performance data and make data-driven decisions Maintain and improve trading software systems and tools Expand the group’s library of modeling, analytics, and automation tools Resolve day-to-day trading issues

Required Qualifications, Capabilities, and Skills:

3 years of experience in Commodities quantitative trading or similar roles Bachelor’s degree in computer science, mathematics, physics, engineering, or other quantitative fields Strong programming skills in Java/C++ or other object-oriented languages Excellent research skills Attention to detail, adaptable, driven, and collaborative Strong interest in markets and systematic trading

Preferred Qualifications, Capabilities, and Skills:

Foundational knowledge of statistics and data analysis techniques Interest or experience in market microstructure and systematic trading Knowledge of order types, L2 market data, and central limit order books Experience with KDB+/q and Python