Quantitative Arbitrage Trader - Proprietary Desk

Job Description

We are seeking an exceptional Arbitrage Trader with a strong foundation in quantitative trading to join our proprietary desk. This role is ideal for someone who can leverage data, technology, and statistical methods to identify and execute high-probability arbitrage opportunities across markets.

As part of our high-performing team, you will be empowered to innovate, take ownership of your trading strategies, and benefit from a performance-driven environment backed by cutting-edge infrastructure and capital support.

Key Responsibilities :

- Design, develop, and manage quantitative arbitrage strategies across asset classes.

- Leverage market inefficiencies and pricing anomalies through automated and semi-automated strategies.

- Continuously enhance strategy performance using statistical analysis, back-testing, and real-time monitoring.

- Risk management, including position sizing, exposure monitoring, and performance attribution.

- Stay updated with market structure changes, regulatory developments, and technological shifts impacting trading efficiency.

Skills & Requirements:

- Proven track record in quantitative arbitrage trading at a proprietary desk, hedge fund, or HFT setup.

- Strong understanding of quantitative models, market micro-structure, and statistical methods.

- Hands-on experience with Python (preferred), R, C++, or similar languages for strategy development and automation.

- Ability to process large datasets, draw actionable insights, and build logic-driven trading frameworks.

- Solid grasp of risk control methodologies and real-time risk monitoring.

- Ability to make rational and fast decisions in high-stakes market environments.

- Consistent composure during volatile market conditions.

- Eagerness to learn, iterate, and evolve strategies in line with market dynamics.

- Familiarity with trading platforms, APIs, market data systems, and low-latency environments.

- Comfort working in cross-functional teams with developers, researchers, and risk professionals.

- Bachelors or Masters degree in Finance, Economics, Mathematics, Statistics, Engineering, Computer Science, or related field.

- Advanced qualifications (CFQ, FRM, CMT) are a plus.