Quantitative Researcher

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 a Quantitative Researcher to develop and enhance data-driven trading strategies across global financial markets.

You will work with large-scale datasets, apply statistical and quantitative techniques to generate predictive signals, and collaborate closely with trading and engineering teams to improve strategy performance and scalability.

This is a high-ownership role with end-to-end involvement in quantitative research and strategy development.

What You’ll Do

• Research and develop data-driven quantitative trading strategies.

• Analyze large-scale financial and market datasets to identify patterns and trading opportunities.

• Develop and evaluate predictive signals using statistical and quantitative techniques.

• Apply probability, statistics, and data analysis to research and strategy development.

• Translate research ideas into robust and scalable trading strategies.

• Collaborate closely with trading and engineering teams to improve strategy performance and scalability.

• Take ownership of research projects from initial analysis through implementation and evaluation.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related quantitative field.

• Strong problem-solving and quantitative skills.

• Solid understanding of probability, statistics, and data analysis.

• Proficiency in Python; knowledge of C++ is an advantage.

• Strong knowledge of data structures and algorithms.

• Experience working in Linux/Unix environments.

• Ability to work effectively in a fast-paced, research-driven environment.

• Strong communication skills and a high degree of ownership.