ABOUT EXODUSPOINT

ExodusPoint Capital, founded in 2017 by Michael Gelband, began managing investor capital in 2018. The firm employs a global multi-strategy investment approach, seeking to deliver compelling asymmetric returns by combining complementary liquid strategies managed by experienced investment professionals within a robust risk framework. ExodusPoint brings together an accomplished team with hands-on experience running multi-manager businesses to create an institutional investment management firm.

Quantitative Research Intern – Systematic FICC - Hong Kong

About the Team

The Systematic Rates team researches and runs fully systematic, data-driven strategies in global interest FICC markets. We combine solid statistics, careful engineering and a good feel for how markets work to build and improve systematic trading strategies.

The Role

You'll work closely with the portfolio manager. You'll do hands-on research and development across the whole strategy process, and you'll own real projects with real impact, not side tasks.

Responsibilities

• Research, prototype and backtest systematic strategies across FICC products such as swaps and foreign exchange.
• Build and maintain production pipelines, research tools and analytics libraries.
• Run statistical analysis on market data: signal research, factor analysis, regime analysis, and transaction cost and capacity studies.
• Help monitor and analyse the performance and risk of live strategies.
• Write clean, tested, well-documented code that the team can rely on and reuse.

Requirements

• Strong coding skills. You're proficient in Python (or a similar language). You can design, write, debug and explain your own code. We expect real engineering ability, not just prompting AI tools for code you can't reason about.
• Strong math and statistics. You're comfortable with probability, linear algebra, regression and time-series analysis.
• Basic knowledge of financial instruments. You understand FICC market at a foundational level, and you're keen to learn more.

Nice to Have

• Experience on a fixed income or rates desk (trading, research or strategy). This is a plus, not a requirement.
• Experience with pandas, NumPy, SciPy, statsmodels or similar, plus SQL and version control (Git).
• Experience with backtesting frameworks, or with large and messy financial datasets.

Availability

• Start date is as soon as possible.
• Full-time placement preferred for a season (e.g., an off-cycle).
• Duration will be 3 - 6 months in our Hong Kong office
• Part-time candidates can be considered who can commit to at least 4 days a week.