Hedge Fund Quantitative Analyst

Umbrex; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

Umbrex seeks an experienced Hedge Fund Quantitative Analyst to help design and implement a machine-learning powered equity trading engine. You will build alpha-generation strategies and apply advanced models to equity markets.

Work closely with the founder in a hands-on startup-like environment, writing production-ready Python code and validating models in live markets. Candidates bring portfolio and market risk analysis expertise and a track record in quantitative investing, ideally within

Qualifications

• Experience in quantitative investing, research, or trading, preferably in hedge funds or asset managers.
• Direct experience with equities and strong knowledge of equity markets.
• Experience with hedge fund–style investing or systematic portfolio management.
• Strong portfolio risk analysis and market risk-factor modeling skills.
• Hands-on development of quantitative or machine-learning models.

Responsibilities

• Design, test, and optimize ML-driven equity trading models.
• Develop alpha-generation and alpha-capture strategies.
• Apply non-linear models and neural networks to equity markets.
• Analyze portfolio and market risk factors for strategy resilience.
• Contribute to architecture, implementation, and scaling of the trading engine.
• Write production-ready Python code and use AI-assisted coding tools to accelerate work.
• Monitor model performance and continuously improve the system.
• Collaborate closely with the founder and team in a startup-like environment.

Skills

Quantitative investing

Equities

Portfolio risk analysis

Machine learning

Python programming

Data analysis

Tools

Cursor AI-assisted coding tool

Python

Job description

Our client is building a machine-learning-powered equity trading engine and is seeking an experienced Hedge 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
• 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.
• Experience using AI-assisted coding tools for code development, testing, or debugging is preferred.