Quantitative Analyst Intern
Skills
About the Role
You will develop modular Python-based quant libraries (using Pandas, NumPy, and Polars), perform deep-dive statistical analysis on trade-level data to decompose PnL drivers and surface execution issues, analyze Perpetual DEX incentive structures to improve capital efficiency, build automated workflows that convert order book data into insights, and proactively monitor market microstructure and portfolio exposures.
Requirements
- Recent or upcoming graduate in financial engineering, mathematics, physics, computer science, or related quantitative field
- Proficiency in Python for data science
- Experience with SQL
- Exposure to Rust or strong desire to learn Rust
- Strong background in probability, statistics, and linear algebra
- Track record running automated or semi-automated trading strategies
- Working knowledge of equity market structure and Perpetual DEX dynamics
- Fluency in English
Responsibilities
- Develop modular Python quant libraries for performance metrics and trading data
- Analyze trade-level data to decompose PnL drivers and isolate alpha decay
- Optimize Perpetual DEX participation and incentive-driven strategies
- Build and maintain automated workflows to transform L1/L2 order book data into actionable insights
- Monitor market microstructure signals and portfolio exposures to identify risks and liquidity opportunities
Benefits
- 6 month paid internship
- Hybrid work setup in London or Brussels offices
- Company and team wide offsites
- Opportunity to work in a global, tech-driven environment
- Autonomy and direct impact from day one