Free Data Science Meetup at ODSC East 2018

We are very excited to host two incredible speakers for a Meetup during the East 2018 Open Data Science Conference at Boston Convention Center in Room 204B.

Schedule:
6:00pm - 6:15pm - Check-in
6:15pm - 6:45pm - Speaker Allen Downey, PhD
6:45pm - 6:50pm - 5 minute Q&A
6:50pm - 7:20pm - Jeffrey Yau, PhD
7:20pm - 7:25pm - 5 minute Q&A
7:25pm - 8:00pm - Networking

Allen Downey, PhD Bio:
https://www.linkedin.com/in/allendowney/

Allen Downey is a professor of computer science at Olin College and author of Think Stats, Think Bayes and several other books about computation and engineering. He writes a blog, called "Probably Overthinking It", about data science and Bayesian statistics.

Title of Talk:
Data Science, Data Optimism.

Abstract:
Data Science is a toolkit for using data to answer questions and guide decision making under uncertainty. But this approach to data science is based two assumptions: that it is possible for data to answer questions and resolve debates, and that we make better decisions when they are based on evidence and reason. In a "post-truth" world, that stance might seem naive, but in this talk, I argue that is it not only still true; it is truer than ever.

I present examples from my research and my classes where data, simple statistical methods, and effective visualization make it possible to inform and influence public debate. And I suggest ways data scientists can use their skills to make a positive change in the world.
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Jeffrey Yau, PhD Bio:
https://www.linkedin.com/in/jeffreyyau/

Title of Talk: Creating Robust Data Science Capabilities in an Asset Management Firm.

Note: this is a non-technical, strategy-focused talk.

Abstract:
This talk discusses some of the principles of creating robust data science capabilities in an asset management firm based on my personal experience as well as those of my contacts in other firms. I will outline the key ingredients of a data science stack, which will also include a discussion on (1) the modern data science technology and how they are compared to traditional tools used by investment professionals, (2) machine learning techniques and statistical methods, and (3) how to attract and maintain talents. The talk will be concluded with my personal perspective on potentials of using data science in investment management and the potential challenges ahead.

Target Audience: C-level and VP-level executives who want to build data science capabilities in an asset management firm.