I am an applied mathematician/data scientist with over 16 years of industrial experience. My skills cover idea generation, modeling, testing, and implementation.
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I have led projects that include high-frequency trading, statistical DNA reconstruction, negotiation modeling, natural language processing, programming language development, and a variety of machine learning methods for predictive modeling.
I have expert knowledge of mathematics, statistics, probability, machine learning, computer architecture, algorithms, and several...
I offer the following services:
--Building predictive models on big data
--Building predictive models on small data
--Analytics pipeline design and database schema design
--Data cleaning and standardization
--Advising on experimental design when gathering data
--Clear presentation of results to non-technical audiences
Some cool projects I've done in the past:
--Built a fully automated model that predicts US Supreme Court justice votes better than the best human predictors, based on natural language processing (75% accurate and improving)
--Created an algorithm to identify the host organism of an unknown, fragmented DNA sample (30x faster than previous state of the art)
--Developed successful automated trading strategies
--Established a model to exploit arbitrage between betting venues
--Formulated provably optimal strategies in structured negotiations
--Modeled urban real estate markets
--Built a realistic model of birds flocking
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U.S. Securities and Exchange Commission
Senior Science Adviser
2012 - 2015
•Creator of the Machine Analyzed Risk Scoring (MARS) project, which
quantifies investment adviser risk by using machine learning techniques on a
range of structured and unstructured data sources to...
ION Trading High Frequency Fund
2010 - 2012
•Traded Eurodollar products at CME. Designed and wrote live algorithms.
•Modeled Eurodollar futures markets: spread/underlying statistical arbitrage,
mean reversion, momentum, gamma scalping,...