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 chance 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 Strategist to design, implement, and optimize data-driven trading strategies across global markets, with a focus on derivatives and crypto markets.

You will work with large-scale datasets, apply advanced statistical and machine learning techniques to identify trading opportunities,



and translate research ideas into optimized, production-quality strategies.

This is a high-ownership role with involvement across the full strategy lifecycle, from research and signal development to back testing, implementation, production, and continuous optimization.

Research → Signal Development → Back testing → Implementation → Production → Optimization

What You’ll Do
- Research and develop quantitative trading strategies using large-scale financial and market datasets.
- Apply advanced statistical and machine learning techniques to identify patterns, signals, and potential trading opportunities.
- Research predictive signals and features to support alpha generation and strategy development.
- Design, test, and implement trading strategies in optimized, production-quality code.
- Perform rigorous back testing and evaluate strategy performance across different market conditions.
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📌 Quantitative Researcher (Gurugram)
🏢 Quadeye
📍 Gurugram