Quantitative Researcher - Machine Learning / Data Science

About the company: Quadeye is an algorithmic trading firm operating across all major financial markets and exchanges. We specialize in transforming deep market insights into sophisticated, automated trading strategies across diverse asset classes. By combining advanced mathematical models with cutting-edge technology, we build scalable, resilient, and high-performance trading systems. Our meritocratic culture empowers engineers and researchers to take complete ownership, drive innovation, and make a direct impact on trading performance. With access to world-class infrastructure, mentorship, and real-time feedback, our team thrives on solving some of the toughest problems in quantitative finance. Role Overview: We are looking to hire Quantitative Researchers who can apply advanced mathematical and statistical techniques to develop and test automated strategies. This team is responsible for combining the machine-driven data analysis with the human thought in order to make sense out of terabytes of data and identify trading opportunities. We are looking for researchers with a keen interest and potential of applying quantitative research in trading. What You'll Work On: Using advanced statistical and machine learning techniques to predict and test market patterns Creating novel formulation of existing ML techniques to design systems capable of producing trading signals around a fundamental economic concept Contribution across a wide range of trading tasks like alpha generation, portfolio construction/optimization and regime identification Run back tests and implement created models into productionizable code Productionize the strategies; investigate, observe and devise new ideas for better and faster predictions Build infrastructure around successful prototypes for use across the board and deliver productionizable implementation ​ What We're Looking For: Engineering degree in Computer Science/Maths/Stats or equivalent from Premier Institutes Good problem-solving skills and quantitative aptitude Strong background in data structures, algorithms and object-oriented programming, preferably in C++ or C Detailed knowledge of Python and R Experience with popular ML libraries and associated cloud infrastructure is a plus Working knowledge of Linux Strong work ethics and communication skills Ability to manage multiple tasks in a fast-paced environment