Oualid is a quantitative researcher/data scientist with a decade experience applying statistical machine learning and predictive modeling techniques to tackle a variety of financial problems including optimal trade execution, short-term alpha modeling, alpha amplification as well as algorithmic credit trading. He is currently a senior data scientist with Jefferies focusing on building ML based solutions for fixed income credit algorithmic trading and capital-structure events forecasting. Prior to Jefferies, he built the prediction engine behind Portware LLC award winning AlphaPro trading automation platform. He earned master’s degrees in both signals & systems engineering and applied mathematics from Polytechnic School of Tunisia. He also holds a PhD in Artificial Intelligence from University of Louisville where he conducted research on machine learning based algorithms for landmine detection.
- Understanding what systematic signals or information is contained in microstructure data
- Assessing preliminary microstructure analysis and liquidity
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