Key responsibilities

• Conduct rigorous quantitative research to identify patterns, inefficiencies, and opportunities within large financial and alternative datasets.
• Design, implement, and test systematic trading models using advanced statistical, mathematical, and machine learning techniques.
• Develop and maintain high-quality, production-level code to support research, backtesting, and live trading systems.
• Perform large-scale data analysis, including cleaning, transformation, feature engineering, and validation of structured and unstructured datasets.
• Build and enhance research infrastructure, including simulation frameworks, optimization tools, and performance evaluation systems.
• Collaborate with researchers, developers, and technology specialists to integrate models into scalable and efficient trading platforms.
• Apply scientific experimentation principles, including hypothesis testing, validation, and robustness checks, to ensure research integrity and reproducibility.
• Continuously improve algorithm efficiency and computational performance using high-performance computing techniques.
• Document research findings, methodologies, and implementation details clearly to ensure knowledge sharing and long-term maintainability.
• Stay up to date with advances in quantitative finance, mathematics, statistics, computer science, and related disciplines to incorporate innovative techniques into research workflows.
• Contribute to a collegial, multidisciplinary environment by sharing knowledge, mentoring peers where appropriate, and participating in collaborative problem-solving sessions.