Quantitative Researcher (Equities & Machine Learning)
About the Role:
We are seeking a highly skilled Quantitative Researcher to join our team, focused on developing and enhancing systematic equity strategies. This role sits at the intersection of financial theory, data science, and machine learning, and is ideal for candidates with a strong academic background and a passion for applying advanced quantitative methods to real-world markets.
Key Responsibilities
- Develop and implement quantitative models for equity markets, including alpha generation and risk modeling
- Apply machine learning techniques to large financial datasets to uncover predictive signals
- Conduct rigorous backtesting and performance analysis of trading strategies
- Collaborate with portfolio managers and engineers to translate research into production
- Continuously monitor and improve model performance in live trading environments
- Stay up to date with academic research and emerging trends in quantitative finance and machine learning
Requirements
- PhD in a quantitative field (e.g., Mathematics, Physics, Computer Science, Statistics, Financial Engineering, or related discipline)
- Strong experience in equities markets and systematic strategies
- Solid understanding of machine learning techniques and their application in finance
- Proficiency in programming (Python required; experience with C++ or similar is a plus)
- Experience with large datasets and data analysis tools
- Strong problem-solving skills and attention to detail
Preferred Qualifications
- Experience working in a hedge fund, asset management, or proprietary trading environment
- Familiarity with alternative data sources and feature engineering
- Knowledge of portfolio construction and risk management techniques
- Track record of published research or applied work in quantitative finance or machine learning
