Richard Liao is a data science manager in New York with nine years of experience applying advanced ML, Bayesian time-series, NLP, and network analysis to detect market abuse and supervisory risk in financial services. At FINRA he leads a cross-functional team building behavior-based risk models, firm liquidity models, and human-centered, interpretable AI solutions while accelerating delivery with Spark, Airflow, and modern web stacks. Previously he helped found the SEC’s Quantitative Analytics Unit and led development of the National Exam Analytics Tool and high-frequency analytics for large-scale trade surveillance. His background in quantitative finance and HFT strategy design at major banks and trading firms gives him rare domain fluency across markets, regulation, and production ML. He maintains a deep learning research blog and active GitHub showcasing work in NLP, computer vision, and finance, reflecting both research rigor and hands-on engineering. Colleagues rely on him to translate complex analytical ideas into auditable, operational systems that balance performance, transparency, and regulatory needs.
10 years of coding experience
1 year of employment as a software developer
Master's degree, Computational Finance, Master's degree, Computational Finance at Carnegie Mellon University - Tepper School of Business
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