Quantitative Researcher - Commodity, Derivatives , Crypto and India Options

About Quadeye Quadeye is an algorithmic trading firm operating across major global financial markets and exchanges. We combine quantitative research, advanced mathematical modeling, and high-performance technology to develop sophisticated automated trading strategies across diverse asset classes. Our teams work at the intersection of markets, mathematics, statistics, and technology, with significant ownership across the entire strategy lifecycle—from research and ideation to implementation, deployment, and optimization.

We offer a highly meritocratic environment where talented researchers and engineers have the opportunity to work on challenging problems, access world-class infrastructure, and see the direct impact of their work on live trading performance. The Role We are looking for experienced Quantitative Strategists to research, design, implement, and optimize systematic trading strategies across global financial markets.

You will work with large-scale market datasets, apply advanced statistical and machine learning techniques to identify trading opportunities, and translate successful research into highly optimized production code. You will have ownership across the strategy lifecycle, from developing and testing ideas to deploying them in live markets and continuously improving their performance.

This is a high-ownership role where you will contribute across the entire strategy lifecycle: Research → Signal Development → Backtesting → Implementation → Production → Optimization What You’ll Do

• Analyze large-scale market datasets using advanced statistical and machine learning techniques to identify systematic trading opportunities.
• Research and develop predictive signals and data-driven trading strategies across global financial markets.
• Design, implement, and optimize trading strategies in high-performance, production-ready code.
• Build rigorous backtests to evaluate strategy performance and robustness across different market conditions.
• Take successful strategies from research and prototyping through implementation and live production deployment.
• Monitor live strategy performance, investigate outcomes, and identify opportunities for continuous improvement.
• Develop new approaches to improve the accuracy, speed, and efficiency of trading predictions.
• Collaborate with researchers, traders, and engineers to improve strategy performance and the supporting research and trading infrastructure.

Requirements

• Engineering degree in Computer Science or a related quantitative discipline, preferably from a leading academic institution.
• Strong quantitative aptitude with excellent analytical and problem-solving skills.
• Strong foundation in data structures, algorithms, and object-oriented programming.
• Proficiency in C++ or C, with the ability to write efficient, high-performance code.
• Understanding of statistical analysis and quantitative methods for working with large-scale datasets.
• Working knowledge of Linux-based environments.
• Knowledge of Python, R, or Perl for quantitative analysis and research is advantageous.
• Exposure to statistical modeling or machine learning techniques is desirable.
• Ability to translate quantitative ideas into robust, production-ready implementations.
• Ability to manage multiple priorities and work effectively in a fast-paced environment.
• Strong communication and collaboration skills with a high degree of ownership.