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:

1. Equity markets and the relevant asset class
2. Hedge fund–style quantitative investing
3. Portfolio and market risk analysis

1. Design, test, and optimize machine-learning-driven equity trading models.
2. Develop and refine alpha-generation and alpha-capture strategies.
3. Apply non-linear models, neural networks, tree-based models, and other advanced quantitative techniques to equity markets.
4. Analyze portfolio risk, market risk factors, and strategy resilience.
5. Contribute to the architecture, implementation, and scaling of the trading engine.
6. Write efficient, production-ready code, primarily in Python.
7. Use AI-assisted development tools, such as Cursor or similar platforms, to accelerate coding, testing, and debugging.
8. Monitor model and strategy performance, troubleshoot issues, and continuously improve the system.
9. Work closely with the founder and broader team in a hands-on, startup-like environment.

1. Professional experience in a quantitative investing, research, or trading role, ideally within a hedge fund, asset manager, or proprietary trading firm.
2. Direct experience with equities and a strong understanding of equity markets.
3. Demonstrated exposure to hedge fund–style investing, quantitative trading strategies, or systematic portfolio management.
4. Strong experience with portfolio risk analysis and market risk-factor modeling.
5. Hands-on experience developing quantitative or machine-learning models.
6. Knowledge of non-linear models, neural networks, and ensemble or tree-based methods.
7. Strong Python programming skills.
8. Experience using AI-assisted coding tools for code development, testing, or debugging is preferred.