Quantitative Researcher - Romania
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 seeking an exceptional Quantitative Researcher to join our dynamic research team. This role involves end-to-end quantitative research—from idea generation and alpha discovery to model development, validation, and production deployment. The ideal candidate has deep expertise in statistical modeling and machine learning, with a strong inclination toward translating research insights into robust, monetizable trading systems.
What You’ll Work On
Alpha & Feature Research:Develop, test, and enhance alpha signals and features using large-scale market data and alternative data sources. Explore new research directions to uncover actionable market insights.
Statistical Modeling:Build and refine predictive models covering the full research lifecycle, including data preprocessing, feature selection, model design, and validation using techniques such as regularization, cross-validation, and ensemble methods.
Model Combination & Validation:Research and implement model combination techniques (e.g., model averaging, stacking) to improve robustness and performance across market regimes.
Production & Post-Trade Analysis:Analyze live trading performance, conduct post-trade diagnostics, and continuously optimize models to maximize risk-adjusted returns.
Collaboration:Work closely with trading and engineering teams to enhance research methodologies, data pipelines, and infrastructure while contributing to a strong culture of knowledge sharing.
What We’re Looking For
Experience:Strong background in statistical modeling, machine learning, and data analysis applied to real-world problems.
Programming Skills:Proficiency in Python, C++, R, or similar languages, with hands-on experience using libraries and frameworks such as NumPy, Pandas, SciPy, scikit-learn, TensorFlow, or PyTorch.
Education:A degree in a quantitative discipline such as Mathematics, Statistics, Computer Science, Physics, AI/ML, or a related field.
Core Skills:
Excellent problem-solving ability with a strong mathematical and statistical foundation
Experience working with time-series data, financial markets, and market microstructure
Strong communication skills and the ability to collaborate effectively with traders and engineers