Mark Cleverley is a data scientist at SFL Scientific. After a degree in Statistical Economics and Political Science from New York University, he progressed through the Flatiron School’s postgraduate data science program working in areas of computational data science including topics in computational analysis, uncertainty quantification, Bayesian statistical tools, high performance computation, and emerging AI techniques. Mark has significant expertise in deep learning and statistical analysis, and has worked with multiple clients to generate call-targeting software and oversee AWS-based pipeline maintenance. He is particularly focused on graph networks and neuromorphic sparse AI architectures.
Prior to joining SFL Scientific, Mark worked as a data science instructor with Trilogy Education, partnered with the high-frequency-trading firm Intelletic to backtest Temporal Memory binary neural networks and build AI-based cryptocurrency trading algorithms.