Asset managers of all stripes are ramping up their data science capabilities. Andrew Chin and Celia Chen offer an overview of data science applications within the asset management industry, covering case studies spanning different functions within an asset management organization. Along the way, they look at an investment research project that used a new “big dataset” as well as a machine algorithm to create a more powerful prediction model and detail a machine learning model they developed to understand their clients better.
Andrew Y. Chin is the chief risk officer and head of quantitative research for AllianceBernstein, where he oversees all aspects of risk management to ensure that the risks being taken are well understood and appropriately managed and is responsible for the firm’s data science strategy and for optimizing the quantitative research infrastructure, tools, and resources across the firm’s investing platforms. He’s held a number of quantitative research roles at the firm, in both New York and London, including senior portfolio manager for style blend equities and director of quantitative research for value equities. Prior to joining the firm, he was a project manager and business analyst in global investment management at Bankers Trust. Andrew teaches in the School of Operations Research and Information Engineering at Cornell University and leads teams of students on capstone projects utilizing quantitative and data science skills to address investment issues. He holds a BA and an MBA from Cornell University.
Celia joined AB in April 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.
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