Head of Quant Trading

About the Company

A founder-led, well-capitalized proprietary trading firm built around real-time, data-driven decision-making. The team values curiosity, collaboration, and a bias toward action. Following years of success through discretionary trading, the firm is launching a dedicated quantitative trading division and is seeking a senior quantitative leader to build and scale the function from the ground up.

Role Summary

This individual will lead the development, optimization, and deployment of algorithmic trading strategies and quantitative models. The role combines hands-on research and engineering with strategic oversight across trading, infrastructure, and quantitative operations.

Key Responsibilities

Quantitative Research & Strategy Development

• Design and enhance proprietary algorithmic trading strategies using statistical and machine learning techniques.

• Develop forecasting, signal generation, and risk models, supported by robust backtesting and simulation frameworks.

• Analyze large and diverse datasets, including market and alternative data sources, to identify actionable opportunities.

• Evaluate and apply emerging quantitative research, including deep learning, reinforcement learning, and other advanced modeling techniques.

Technology & Infrastructure

• Partner with engineering teams to build and scale high-performance trading systems.

• Oversee development across Python and C++ environments, promoting strong software engineering standards, testing, and deployment practices.

• Build and maintain data pipelines for ingestion, research, model training, and production deployment.

• Evaluate and implement analytics tools, databases, cloud infrastructure, and third-party technologies as needed.

Performance & Risk Management

• Establish and monitor key performance metrics including alpha generation, execution quality, risk-adjusted returns, drawdowns, and latency.

• Develop and maintain robust risk management frameworks and controls.

• Conduct ongoing model validation, scenario analysis, and strategy optimization.

Leadership & Collaboration

• Build, mentor, and lead a team of quantitative researchers, data scientists, and engineers.

• Foster a culture of experimentation, collaboration, and rigorous research practices.

• Promote high-quality, maintainable code and transparent research documentation.

Qualifications

• Bachelor's or Master's degree in Mathematics, Computer Science, Engineering, Statistics, Physics, or a related quantitative discipline.

• Experience developing and deploying profitable algorithmic trading strategies within a hedge fund, investment bank, market-making firm, or proprietary trading environment.

• Strong programming skills in Python, C++, Java, or similar languages, along with experience working in Linux-based environments and modern development workflows.

• Deep understanding of statistics, machine learning, and quantitative modeling techniques.

• Experience building real-time data pipelines, distributed systems, cloud infrastructure, and performance-critical applications.

• Strong communication skills and the ability to operate effectively in a fast-paced, highly collaborative environment.

• Demonstrated leadership capabilities with the ability to build teams and drive initiatives from inception through execution.

What the Firm Offers

• Opportunity to help build a quantitative trading and research function from the ground up.

• Significant ownership and influence over strategy, technology, and team development.

• Competitive compensation with substantial performance-based upside.

• Environment focused on intellectual curiosity, rapid learning, and long-term value creation.

• Access to a differentiated market perspective and research-driven approach to trading.