About the Job
Our client is building a machine-learning-powered equity trading engine and is seeking an experiencedHedge Fund Quantitative Analyst to support its design, development, and implementation.
The ideal candidate combines expertise across three core areas:
• Equity markets and the relevant asset class
• Hedge fund–style quantitative investing
• Portfolio and market risk analysis
Responsibilities
• Design, test, and optimize machine-learning-driven equity trading models.
• Develop and refine alpha-generation and alpha-capture strategies.
• Apply non-linear models, neural networks, tree-based models, and other advanced quantitative techniques to equity markets.
• Analyze portfolio risk, market risk factors, and strategy resilience.
• Contribute to the architecture, implementation, and scaling of the trading engine.
• Write efficient, production-ready code, primarily in Python.
• Use AI-assisted development tools, such as Cursor or similar platforms, to accelerate coding, testing, and debugging.
• Monitor model and strategy performance, troubleshoot issues, and continuously improve the system.
• Work closely with the founder and broader team in a hands-on, startup-like environment.
Qualifications
• Professional experience in a quantitative investing, research, or trading role, ideally within a hedge fund, asset manager, or proprietary trading firm.
• Direct experience with equities and a strong understanding of equity markets.
• Demonstrated exposure to hedge fund–style investing, quantitative trading strategies, or systematic portfolio management.
• Strong experience with portfolio risk analysis and market risk-factor modeling.
• Hands-on experience developing quantitative or machine-learning models.
• Knowledge of non-linear models, neural networks, and ensemble or tree-based methods.
• Strong Python programming skills.
• Experience using AI-assisted coding tools for code development, testing, or debugging is preferred.
