Quadeye is a leading algorithmic trading firm with its presence across all global exchanges specializing in cutting-edge quantitative strategies and market making. Our team is dedicated to driving innovation in financial markets through advanced statistical models, data science, and algorithmic execution. We pride ourselves on fostering a collaborative environment where technical expertise and creative problem-solving are at the forefront of our trading strategies.
We are seeking an exceptional Quantitative Researcher to join our dynamic research team. The ideal candidate will have a strong background in alpha and feature research, statistical modeling, and the end-to-end process of taking models from development to production. This role will involve research, model design and implementation, as well as post-trade analysis to optimize and monetize our trading systems to their fullest potential.
Key Responsibilities:
- Alpha & Feature Research: Develop, test, and enhance alpha signals and features using market data and various alternative data sources. Investigate new research areas to identify and extract actionable insights from the market.
- Statistical Modeling: Lead efforts in building and refining statistical models to predict market behavior. This includes everything from feature selection and data preprocessing to model selection and validation techniques (e.g., regularization, cross-validation, ensemble methods).
- Model Combination & Validation: Explore and implement methods for combining models, leveraging techniques such as model averaging or stacking to improve predictive performance and robustness.
- Production Implementation: Work closely with the engineering team to deploy and integrate models into the live trading environment. Ensure that models are optimized for low-latency execution and maintainable in a fast-paced, evolving environment.
- Post-Trade Analysis: Perform detailed post-trade analysis to assess model performance and identify areas for improvement. Debug and troubleshoot issues that arise in live trading and contribute to system improvements.
- System Monetization: Identify opportunities to improve the profitability of trading strategies through optimization, parameter tuning, and the identification of market inefficiencies. Ensure models are operating at their full potential in real-time markets.
- Collaboration: Collaborate with trading and engineering teams to continuously improve research methods, data pipelines, and infrastructure. Share insights and foster a knowledge-sharing culture.
Job Location: New York
Ideal candidate should have:
- Strong experience in quantitative research, particularly in alpha and feature development for high-frequency or algorithmic trading
- Extensive experience in statistical modeling, machine learning, and data analysis techniques
- Proficiency in programming (Python, C++, R, or similar) with experience in tools like NumPy, SciPy, Pandas, and machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
- Experience in taking models into production, with a strong understanding of performance, latency, and system architecture considerations
- Education: A degree in a quantitative field such as Mathematics, Statistics, Computer Science, Physics, Engineering, or similar
Skills :
- Excellent problem-solving abilities with a strong mathematical/statistical foundation
- Experience with time-series analysis, market microstructure, and financial data
- Ability to analyze trading strategies, debug systems, and implement improvements through detailed post-trade analysis
- Strong communication skills and the ability to collaborate with cross-functional teams, including traders and engineers
Preferred Skills:
- Experience in high-frequency trading or market-making environments
- Familiarity with low-latency programming and optimization techniques
- A proven track record of applying research to drive improvements in live trading systems
Top Skills
What We Do
Quadeye combines the best of both worlds: the opportunity and spirit of a startup and the stability of an established, experienced firm. Our employees work hard to solve interesting problems, and their results are rewarded. We value continuous learning—from our outcomes, from the environment and from each other.
By having deepest possible understanding of the financial markets and translating that understanding into great automated trading strategies, we have built a distinct track record of success. We trade across many asset classes and instruments, using a variety of models, across the globe.
