Intern - Quant Researcher

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 sharp, curious, and driven Quantitative Strategist Interns to work at the intersection of mathematics, programming, and financial markets. You will conduct hands-on quantitative research, analyze market data, and contribute to ideas that can directly influence our trading strategies and the technology powering our live trading systems. This internship is designed for students who enjoy analytical thinking, problem-solving, quantitative research, and coding, and want to apply these

skills

to real-world financial markets. You will work in a fast-paced, collaborative environment where you can take ownership of meaningful problems and see your ideas translate into real trading impact. Research → Data Analysis → Signal Development → Backtesting → Implementation → Trading Impact What You’ll Do

• to real-world financial markets. You will work in a fast-paced, collaborative environment where you can take ownership of meaningful problems and see your ideas translate into real trading impact. Research → Data Analysis → Signal Development → Backtesting → Implementation → Trading Impact What You’ll Do
• Conduct quantitative research using mathematical, statistical, and programming techniques to explore trading opportunities.
• Explore financial research and market literature to generate new trading ideas and rigorously backtest them.
• Analyze large-scale datasets, market patterns, market microstructure, and strategy performance to generate actionable insights.
• Develop and test quantitative models and signals that can contribute to systematic trading strategies.
• Improve existing research methodologies, tools, and technology to make the research process more robust and efficient.
• Build models and tools that support current and future trading requirements.
• Develop functionality and features that contribute to Quadeye’s research and trading systems.
• Collaborate with quantitative researchers and engineers to translate promising research ideas into practical implementations

Requirements

• Pursuing an engineering degree in Computer Science or a related quantitative discipline, preferably from a leading academic institution.
• Strong quantitative aptitude with excellent analytical and problem-solving skills.
• Solid foundation in data structures, algorithms, and object-oriented programming.
• Strong programming fundamentals, preferably in C++ or C.
• Strong interest in quantitative research, financial markets, and systematic trading.
• Ability to approach complex problems independently and translate ideas into testable solutions.
• Familiarity with Linux-based environments is advantageous.
• Knowledge of Python, Perl, or R is a plus.
• Ability to manage multiple priorities and work effectively in a fast-paced environment.
• Strong communication and collaboration

skills

with a willingness to learn and take ownership.

Requirements

• Pursuing an engineering degree in Computer Science or a related quantitative discipline, preferably from a leading academic institution.
• Strong quantitative aptitude with excellent analytical and problem-solving skills.
• Solid foundation in data structures, algorithms, and object-oriented programming.
• Strong programming fundamentals, preferably in C++ or C.
• Strong interest in quantitative research, financial markets, and systematic trading.
• Ability to approach complex problems independently and translate ideas into testable solutions.
• Familiarity with Linux-based environments is advantageous.
• Knowledge of Python, Perl, or R is a plus.
• Ability to manage multiple priorities and work effectively in a fast-paced environment.
• Strong communication and collaboration

skills

with a willingness to learn and take ownership.