Richard
Data Science Manager - DAT - Member Reg
- Role
- Data Science Manager - Dat - Member Supervision at FINRA
- Location
- New York, NY, US
- LinkedIn followers
- 500 followers
About Richard
My deep learning research blog: richliao.github.io GitHub: github.com/richliao Proven talent for aligning business strategy and objectives with established analytical thinking and solutions development paradigms to achieve maximum operational impacts with minimum resource expenditures. Detail and success-focused thought leader with the ability to administer and solve complex business problems, lead the development of proof of concept prototypes, and supervise and administer all operations of teams of data scientists and software engineers to ensure success. Exceptionally dedicated professional with keen interpersonal, communication, and organizational skills, as well as extensive technical expertise.
Experience
Data Science Manager - Dat - Member Supervision
May 2015 — Present · New York, NY, US
Provide supervision, leadership, and direction to a highly skilled team of data scientists and software engineers through employment of advanced analytics and technologies to further advance Finra’s mission. • Research and implement behavior based risky Representatives model using high dimensional categorical data and event sequence embedding techniques • Research and implement firm liquid risk model using Bayesian time series and machine learning techniques • Research and implement text analytics in area of robotic process automation, information extractions and text classification through effective utilization of NLP and deep learning-based language models. • Apply network analysis to identify risky migration network, trade collusion and market manipulation network • Develop and promote human centered AI solutions with model transparency and interpretability. • Design and build analytical web applications to enhance and maximize end user experiences with cutting edge technologies such as React, Material UI and Flask/NodeJS. • Lead the development and optimization of core computational infrastructure and performance by using techniques such as spark cluster, multiprocessing, and airflow.
Education
Carnegie Mellon University - Tepper School of Business
Master's degree, Computational Finance
2006 — 2007
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