Ryan Clark Email & Phone Number

Over 2 years’ professional experience, including Python Developer at BNP Paribas CIB and Junior Investment Analyst at a buy-side advisory firm. 14+ years coding experience including Machine Learning (Neural Networks) projects, Derivatives Pricing, Backtesting Engines, simple Market Making algos, and Monte-Carlo simulations, across Python, Java, C#.Project Details - Neural Network (Genetic Algo): An implementation of Neuro-Evolution of Augmented Topologies (NEAT) to solve a simple popular game. Network weights optimised using genetic alorothm in Java. No external libraries used - Neural Network: Alpha Zero: an implementation of Deep Mind’s revolutionary Alpha Zero methodology into a game similar to chess. The Neural Network generates training data via “self-play”, and uses and Monte-Carlo Tree Search based on outputs of Value and Policy networks. Programmed in Python using TensorFlow (Keras). - Derivatives EV: Scraped options chain data from Yahoo Finance for each SP500 constituent. Constructed all possible combinations of Short Iron Condor derivatives, calculating EV by considering each outcome probability & P&L at expiry. - Fantasy Football Quant Model: Extracted Fantasy Premier League data from API, predicting player performance combining historical data with forward looking models. Simulated each game 10,000 times using Mont-Carlo Simulation, score-lines calculates using Poisson Distribution. Calculated optimal team using these points predictions. - Backtesting Automated Trading Strategy: Created framework for backtesting custom strategies, generating simple buy/sell signals from SMA/EMAs, parameter optimisation using Stochastic Gradient Descent. - Sports Betting Market Making: Developed a simple MM algo for sports betting markets interfacing with MatchBook API, posting bids and offers to show the best price on exchange. Simple hedging by crossing spread.

Listed skills include Recruiting, Contract Recruitment, and Permanent Placement.

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  Bournemouth University

  1St Class