Quantitative Software Engineer
- Architected a Crypto FX arbitrage and liquidity engine from scratch, achieving 30–45% market share and 4x capital growth over three years.
- Designed real-time capital allocation across venues using convex optimization, increasing utilization from 40% to 95%.
- Built dynamic pricing and spread estimation using online learning algorithms, reducing slippage by 50% across volatile FX pairs.
- Engineered cross-venue route optimization using graph algorithms, generating $100K/month additional volume at 67% win rate.
- Refactored latency-critical paths (market data, order execution) to gRPC with Go microservices, reducing end-to-end latency by over 60%.
- Deployed core execution engine in Python on Kubernetes with optimized message queues, scaling throughput 4x over three years.
- Built institutional-grade trading dashboard with real-time metrics, automated rebalancing, and point-in-time analysis, reducing accounting overhead by 70%.
- Engineered 100+ ETL pipelines in Airflow and PySpark for real-time market data across 30+ instruments, reducing processing time by 80%.
- Shipped production APIs in FastAPI with full type safety, CI/CD, and automated testing, enabling 3x increase in daily trade volume.
- Scaled engine to 3 additional markets and OTC liquidity provision through actor-model design patterns, doubling venue coverage.