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 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. • Translate research ideas and predictive components into robust, production-ready trading strategies. • Deploy strategies into production, monitor live performance, and continuously refine predictive components. • Analyze strategy behavior and investigate anomalies to identify potential performance improvements. • Explore new datasets, signals, models, and research ideas to enhance strategy performance. • Evaluate the robustness and scalability of research ideas before and after production deployment. • Iterate rapidly based on research findings and live trading feedback. • Collaborate with quantitative researchers, traders, and engineers across the strategy development lifecycle. • Take end-to-end ownership of research and strategy development from initial hypothesis through production and optimization. Requirements • Engineering degree in Computer Science or a related field from a premier institution. • Strong problem-solving skills and quantitative aptitude. • Solid understanding of data structures, algorithms, and object-oriented programming. • Experience with C++ or C is preferred. • Working knowledge of Linux environments. • Ability to manage multiple priorities and perform effectively in a fast-paced environment. • Strong communication skills and work ethic. • Familiarity with R, Python, or Perl is a plus. • Open to candidates with up to 1 year of relevant technical experience in technology firms or product companies. • Exposure to Asian, US, or other non-European financial markets is a plus.