Director of Data Science & Analytics
Dr. Samuel Franklin is an experienced data science executive with expertise in advanced statistics, machine learning, artificial intelligence, and consumer behavior. As Director of Data Science & Analytics at FullStory, Dr. Franklin leads a fast-growing department of talented analytics professionals creating product features that deliver actionable insights and recommendations before users even think to ask for them. Data Science & Analytics also develops internal tools that help make the company more “bionic”, which is FullStory lingo for “smarter, faster, and more scalable.”
Dr. Franklin graduated from Georgetown University’s McDonough School of Business with a B.S.B.A. in Finance and continued on to Columbia University where he earned an M.A., M.Phil., and Ph.D. in cognitive psychology with a research concentration in behavioral finance. Outside the office, Sam teaches seminars in Big Data, Statistics, and Machine Learning for Emory University and Georgia Tech.
Sam Franklin is speaking at the following session/s
Bionic Data Science and ML using Behavioral Search and Session Replay
FullStory’s mission is to help our users give their users a perfect online experience. We are doing that by providing a high-leverage platform that answers questions, makes suggestions, and induces empathy across organizations to motivate change. Our customers (and the industry at large) have teams of Data Scientists doing amazing, world-changing things. And in much the same way that FullStory is able to act as a bionic force multiplier for product, support and engineering teams - helping them make their products better. So too can FullStory act as a force multiplier for Data Scientists and ML practitioners. By providing the highest fidelity data for customer product interactions, and also (and more interestingly!) by augmenting your workflows with behavioral search and session replay.
Learn how to leverage new tools like Behavioral Search, Segmentation, and Session Replay to enhance your data science workflows, ML models, and data visualizations. We’ll walk through examples. Turning high quality event-based interaction data (via FullStory DataExport) into powerful models.
Product Managers, Data Scientists and fans of data driven decision making. Whether you’ve run a report from a spreadsheet, or done the nitty gritty of data engineering and model training, you will find some value in this talk. Some experience working with ETL pipelines a plus (but not necessary).