My specialty is in applying the most efficient quantitative methods to gain insights into financial products and trading strategies, with the goal of enhancing their performance and better risk management.
Extensive experience with Python (including numpy, pandas, scipy, dask) enable me to carry out fast and scalable hypothesis testing. I developed and deployed projects using supercomputers (in C++ and MPI). Two of my published papers (with co-authors) use reinforcement learning (dynamic stochastic programming or AI).
Teaching audiences of different expertise levels (including MBA and graduate students) and varying sizes (from 10 to 50) honed my presentation and communication skills.