Quantitative Researcher - Machine Learning / Data Science

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 Quantitative Researchers who can apply advanced mathematical, statistical, and machine learning techniques to develop systematic trading strategies and uncover opportunities within large-scale market datasets.

You will combine data-driven analysis with quantitative intuition to identify market patterns, formulate research hypotheses, and translate successful ideas into production-ready trading strategies. You will contribute across alpha generation, portfolio construction, regime identification, backtesting, and strategy optimization.

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

Research → Alpha Generation → Modeling → Backtesting → Production → Optimization

What You’ll Do

• Apply advanced statistical and machine learning techniques to identify, model, and test patterns in financial markets.

• Develop novel applications and formulations of machine learning techniques to generate trading signals around fundamental economic and market concepts.

• Conduct research across alpha generation, portfolio construction and optimization, and market regime identification.

• Design and run rigorous backtests to evaluate the robustness and performance of trading ideas.

• Translate successful research models into reliable, production-ready code.

• Deploy strategies into production, analyze live performance, and continuously investigate opportunities for better and faster predictions.

• Build scalable research infrastructure and tools around successful prototypes for broader use across the team.

• Work closely with researchers, traders, and engineers to take ideas from initial research through production implementation.

Requirements

• Engineering or advanced quantitative degree in Computer Science, Mathematics, Statistics, or a related 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 and reliable code.

• Strong working knowledge of Python and/or R for quantitative research and data analysis.

• Understanding of statistical modeling, machine learning, and their application to large-scale datasets.

• Experience with popular machine learning libraries and frameworks is advantageous.

• Familiarity with cloud infrastructure for quantitative or machine learning workloads is a plus.

• Working knowledge of Linux-based environments .

• Ability to translate research prototypes into robust, production-ready implementations.

• Strong communication and collaboration skills.

• Ability to manage multiple research and development priorities in a fast-paced environment.