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Latest Projects
Trading sports markets involves the buying and selling of sports bets.
Through research and analysis of collected data, I have built several
algorithms that are currently trading on Horse-Racing markets
which are both highly-volatile and highly liquid.
A large-scale system that detects phishing websites using machine learning.
Feature extraction is restricted to the URL only. This project is currently
being integrated to the systems at Netcraft.
About
I am a confident problem solver with extensive programming experience (in particular Python, .NET),
having developed applications for commercial clients from a young age.
My interests lie in the areas of finance, machine learning and trading technology.
I am also interested in algorithmic trading, and have developed several
trading strategies in the sports trading domain.
For my BSc thesis, I built a commercially successful large-scale phishing
detection solution using Python (scikit-learn, NumPy, SciPy) that uses
machine learning to identify threats in real-time.
I will be joining the graduate programme at J.P. Morgan this September,
following a successful 14-month placement during 2015/16.