Cornell-Citi Financial Data Science Seminars: Andrew Chin (Alliance Bernstein)

Description

Please register for the event here: https://cornell.qualtrics.com/jfe/form/SV_6X1NDjRVYj44OMt "Leveraging Data Science in Asset Management" Big data, advanced analytics and high-powered computing have become more prevalent in the asset management industry over the last decade but significant hurdles remain for broad adoption. We will discuss the changes in the industry as well as the challenges and opportunities for market participants. We will also present a few practical examples demonstrating the potential for alternative datasets and advanced techniques to enhance investment returns for asset managers. Speaker Bio: Andrew Y. Chin is Chief Risk Officer and Head of Quantitative Research for AllianceBernstein. As Chief Risk Officer, he oversees all aspects of risk management to ensure that risks being taken are well understood and appropriately managed. In the Quantitative Research role, Chin is responsible for optimizing the quantitative research infrastructure and resources, and for leveraging best practices across and within asset classes. He has held various quantitative research roles in New York and London since joining the firm in 1997. In 2004, Chin became a senior portfolio manager for Style Blend Equities and was named director of Quantitative Research for Value Equities in 2005. He previously spent three years as a project manager and business analyst in Global Investment Management at Bankers Trust. Chin holds a BA in math and computer science and an MBA in finance from Cornell University. Andrew Chin will be joined by Celia Chen of Alliance Bernstein. See her bio below: Celia joined AB in 2017 as a data scientist. She has been working with multiple teams on building machine learning models, applying natural language processing techniques and leveraging other modern data science techniques to gain business insights and integrate alternative datasets to make better and faster investment decisions. After completing her MA in Quantitative Methods with a data science focus at Columbia University, she joined the Data Incubator, a data science fellowship program, to train on cutting-edge data science techniques and technology. She is currently pursuing a MS in Computer Science specializing in machine learning from Georgia Institute of Technology.