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 join our research team and develop data-driven trading strategies across global financial markets.

You will work across the full quantitative research lifecycle—from idea generation and alpha discovery to statistical modeling, validation, production deployment, and performance optimization. You will use large-scale market and alternative datasets, advanced statistical techniques, and machine learning to identify trading opportunities and translate research insights into robust production strategies.

This is a high-ownership role where you will contribute across the entire strategy lifecycle:

Research → Alpha & Feature Development → Modeling → Validation → Production → Optimization

What You’ll Do

• Research, develop, and enhance alpha signals and predictive features using large-scale market and alternative datasets.

• Explore new research directions and datasets to identify actionable market insights and trading opportunities.

• Build and refine statistical and machine learning models across the full research lifecycle, including data preprocessing, feature selection, model development, and validation.

• Apply techniques such as regularization, cross-validation, ensemble methods, model averaging, and stacking to improve model robustness and performance.

• Design rigorous backtests and validation frameworks to evaluate strategies across different market conditions and regimes.

• Analyze live trading performance, conduct post-trade diagnostics, and continuously optimize models and strategies.

• Translate successful research ideas into robust, scalable production trading strategies.

• Work closely with traders and engineers to improve research methodologies, data pipelines, and quantitative infrastructure.

• Contribute to a collaborative research environment through experimentation, knowledge sharing, and continuous improvement.

Requirements

• Strong background in statistical modeling, machine learning, and quantitative data analysis applied to real-world problems.

• Degree in a quantitative discipline such as Mathematics, Statistics, Computer Science, Physics, AI/ML, Engineering, or a related field.

• Strong mathematical and statistical foundation with excellent analytical and problem-solving skills.

• Proficiency in Python, C++, R, or similar programming languages .

• Hands-on experience with quantitative and machine learning libraries such as NumPy, Pandas, SciPy, scikit-learn, TensorFlow, or PyTorch.

• Experience working with large-scale datasets and developing rigorous data analysis and modeling workflows.

• Understanding of time-series analysis and techniques relevant to quantitative modeling.

• Experience with financial markets, market data, or market microstructure is highly desirable.

• Ability to translate research ideas into robust, testable, and production-ready solutions.

• Strong communication skills and the ability to collaborate effectively with researchers, traders, and engineers.