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Quantitative Researcher – Systematic Futures & Commodities

Salary undisclosed

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We are seeking a Quantitative Researcher to join a high-performing team focused on systematic futures and commodities trading. This role offers the opportunity to design, develop, and implement cutting-edge trading strategies while working collaboratively with data scientists, traders, and software engineers to enhance profitability and risk management.

Key Responsibilities

  • Conduct in-depth analysis to identify and exploit trading opportunities in systematic futures and commodities markets.
  • Develop, refine, and implement trading algorithms to maximize profitability across diverse market conditions.
  • Lead projects from signal generation to strategy implementation, leveraging large datasets to identify statistical patterns and predictive signals.
  • Model Refinement & Market Adaptation
  • Regularly update quantitative models and algorithms to respond to evolving market dynamics.
  • Integrate and monitor trading signals within the global trading framework to ensure strategy efficiency and robustness.
  • Work closely with portfolio manager, data scientists, traders, and software engineers to optimize trading strategies and enhance risk management processes.
  • Provide actionable insights and analytical support to portfolio managers and senior stakeholders.
  • Explore new datasets and statistical techniques to enhance the team’s trading edge.
  • Effectively communicate research findings, methodologies, and results within the team and to senior stakeholders.

Qualifications

  • Advanced degree (Master’s or Ph.D. preferred) in Finance, Mathematics, Statistics, Physics, Computer Science, or a related quantitative field.
  • Experience in quantitative trading or research within systematic futures and/or commodities markets.
  • Exposure to high-frequency or medium-frequency trading environments is highly desirable.
  • Proven track record of developing and deploying profitable trading strategies.
  • Strong programming skills, particularly in Python or C++ (experience with R or SQL is a plus).
  • Hands-on experience in algorithm development and working with large datasets.