Traders in financial markets perform tasks that require them to absorb large amounts of data in limited time and make rapid decisions. Time is money and sub-optimal performance can cost firms hundreds of millions of dollars a year. Liquidnet augments the human expert with a variety of technologies, from anomaly detection pattern recognition algorithms to natural language generation and visualizations.
Joint Liquidnet Chief Data Scientist, Tom Doris, PhD, to discuss challenges in adoption and adherence of new technologies by human experts, deconstruct the methods that were effective in overcoming the obstacles, and review similarities across other industries.
Tom Doris is co-founder and CEO of OTAS Technologies, a Liquidnet Company. As Chief Data Scientist at Liquidnet, he also leads the R&D program exploring the application of AI, machine learning and alternative data to the investment process. Previously, he worked on optimized execution and microstructure analytics in the quant trading group at Marshall Wace, and led the exotic equity derivatives quant development team at Bear Stearns/JP Morgan. Tom also spent 5 years as a research and design engineer at Intel, where he received a patent for his work on compiler optimizations targeting non-uniform memory architecture multicore processors. He holds a Ph.D in computer science for work in computational neuroscience.