Quantitative Researcher - All asset classes

About Quadeye

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.

The Role 

We are seeking experienced Quantitative Strategists to design, implement, and optimize data-driven trading strategies for global markets. You’ll work with large datasets, apply advanced statistical and machine learning techniques, and write high-performance code for live deployment.This role offers full ownership of the strategy lifecycle—from research to production—within a fast-paced, collaborative environment. If you're passionate about markets, coding, and making real-time impact, this is the role for you.

What You’ll Do

• Using cutting edge statistical and machine learning techniques to identify opportunities from terabytes of data
  
• Design and implement trading strategies into a highly-optimized and nimble code
  
• Productionize your strategies; investigate, observe and devise new ideas for better and faster predictions
  

Requirements

• 1+ years of professional experience in quantitative trading, quantitative research, systematic trading, financial modeling, or a closely related field.
  
• Bachelor’s, Master’s, or PhD in Mathematics, Statistics, Electrical Engineering, Physics, or a related quantitative discipline.
  
• Strong academic background from a top-tier university or equivalent institution.
  
• Exceptional quantitative aptitude and problem-solving skills.
  
• Strong programming skills in C++ or C; proficiency in Python is a plus.
  
• Solid understanding of statistical modeling, probability, and data analysis.
  
• Experience working with large datasets and developing data-driven models.
  
• Working knowledge of Linux/Unix environments.
  
• Ability to work independently, manage multiple priorities, and perform effectively in a fast-paced environment.
  
• Strong communication skills, intellectual curiosity, and a high degree of ownership.