My primary research tool is Python (numpy, pandas, matplotlib, scikit-learn), but I have worked with a wide range of languages and technologies. I understand the importance of reusability, documentation, version control, testing, and all the best practices. My role is often mainly consulting and prototyping, but I can also write production code. My work is based on traditional financial theory and tools like asset pricing and volatility models, technical indicators or risk metrics, as well as newer research, machine learning and statistical methods. I can help with quant finance research and development.
I am open to traveling or relocating when reasonable relative to project size. I have worked on projects of varying sizes, from several hours to several months – mostly remote, but some on site or combined.
I have been active in the financial markets and worked with financial data since 2006 (for more about my background see the About page).
