Mission
The Quantitative Engineering Department builds the Fund’s technical backbone — data infrastructure, research toolkits, and trading engines — enabling scalable, reproducible, and institution-grade research and execution.
Example Projects
Designed a point-in-time database architecture with full version control and audit trails, supporting empirical rigor.
Delivered a modular Python toolkit covering data access, factor construction, portfolio statistics, and risk diagnostics (VaR, drawdowns, turnover).
Built a multi-method backtest engine (equal weight, mean-variance, inverse volatility, risk parity, max diversification), with embedded cost and liquidity assumptions.
Enforced engineering best practices: Git workflows, unit testing, documentation standards, and centralized code governance.
Example Future Projects
Extend execution simulation capabilities, incorporating order handling, slicing logic, and venue assumptions.
Launch a live paper-trading platform with alerting systems and run-books for operational continuity.
Implement modular design for cross-team usability, ensuring both technical and non-technical teams can leverage infrastructure.
Train new cohorts in engineering standards to ensure seamless continuity and scalability.
