Victor S.Y. Lo

About

<p><span style="background-color: transparent; color: rgb(34, 34, 34);">Victor S.Y. Lo is a seasoned Data Science/AI, Marketing, Risk, and Finance leader with over three decades of extensive consulting and corporate experience employing data-driven solutions in a wide spectrum of business areas</span><strong style="background-color: transparent; color: rgb(34, 34, 34);"> </strong><span style="background-color: transparent; color: rgb(34, 34, 34);">including Customer Relationship Management, Market Research, Advertising Strategy, Risk Management, Financial Econometrics, Insurance, Product Development, Transportation, Healthcare, Operations Management, and Human Resources. He is a pioneer of uplift modeling, a subfield of data science.</span><strong style="background-color: transparent; color: rgb(34, 34, 34);"> </strong><span style="background-color: transparent; color: rgb(34, 34, 34);">He is currently SVP, AI Ethics Leader at Fidelity Investments and previously managed advanced analytics/data science teams in multiple business units at Fidelity and was VP &amp; Manager of Modeling and Analysis at FleetBoston Financial (now Bank of America), and Senior Associate at Mercer Management Consulting (now Oliver Wyman).</span></p><p><br></p><p>For academic &amp; industry services, Victor has served as an elected board member of the National Institute of Statistical Sciences (NISS) and is currently on the editorial board of three academic journals including Harvard Data Science Review (HDSR) and Frontiers in A.I. as well an executive-in-residence at Bentley University. Victor earned a master of science in Operational Research from Lancaster University and a PhD in Statistics from the University of Hong Kong and was a Postdoctoral Fellow in Management Science at the University of British Columbia. He has co-authored a graduate-level econometrics book and a more recent data science textbook titled “<a href="https://www.amazon.com/Cause-Effect-Business-Analytics-Computer/dp/1482216477/ref=sr_1_1?crid=1DM16QQEIQZO7&amp;dib=eyJ2IjoiMSJ9.Ya0150jWK2cMi8tSpVuOz2ACjCB8dWu1ammw3felCWxmuuH0o7EgRNxkPvdDTnKYy0UA-zM4Ki9k9iL_xpN2dA.AtjGxnTeooGCLy6xIr7gl2thxP7i0hYvtQzmlkqmwLc&amp;dib_tag=se&amp;keywords=cause+and+effect+business+analytics+and+data+science&amp;nsdOptOutParam=true&amp;qid=1768859351&amp;sprefix=cause+and+effect+business%2Caps%2C146&amp;sr=8-1" rel="noopener noreferrer" target="_blank" style="color: rgb(17, 85, 204);"><strong>Cause-and-Effect Business Analytics &amp; Data Science</strong></a>,” and published numerous articles in the Data Mining, Marketing, Statistics, Management Science, and AI Ethics literature.</p>