I design and build software for quantitative research, algorithmic trading, and data-intensive financial systems.
My interests lie at the intersection of software engineering, distributed systems, and quantitative finance, with a focus on developing reliable tools and infrastructure for research and automated trading.
- Quantitative Research
- Algorithmic Trading
- Market Data Engineering
- Financial Data Infrastructure
- Data Processing Pipelines
- Backtesting Systems
- Distributed Systems
- Performance Optimization
- Developing tools for quantitative research workflows
- Building scalable market data pipelines
- Designing efficient storage and retrieval systems
- Automating data processing and validation
- Exploring low-latency system design
- Building reusable libraries for financial analytics
- Python
- SQL
- C++
- Java
- PostgreSQL
- ClickHouse
- Redis
- Docker
- Linux
- FastAPI
- Git
- REST APIs
- CI/CD
- Build systems that are simple, reliable, and maintainable.
- Prioritize correctness before optimization.
- Automate repetitive workflows whenever possible.
- Design with scalability and reproducibility in mind.
- Continuously improve through measurement and iteration.
Outside of day-to-day development, I enjoy exploring topics such as:
- Quantitative Finance
- Market Microstructure
- Statistical Modeling
- Distributed Computing
- Systems Programming
- Data Engineering
"Good research starts with reliable software and reliable data."