Presented By O'Reilly and Cloudera
Make Data Work
Sept 29–Oct 1, 2015 • New York, NY
Charles Givre

Charles Givre
Senior Lead Data Scientist, Deutsche Bank

Website | @cgivre

Charles Givre is an unapologetic data geek who is passionate about helping others learn about data science and become passionate about it themselves. For the last five years, Charles has worked as a data scientist at Booz Allen Hamilton for various government clients and has done some really neat data science work along the way, hopefully saving US taxpayers some money. Most of his work has been in developing meaningful metrics to assess how well the workforce is performing. For the last two years, Charles has been part of the management team for one of Booze Allen Hamilton’s largest analytic contracts, where he was tasked with increasing the amount of data science on the contract—both in terms of tasks and people.

Even more than the data science work, Charles loves learning about and teaching new technologies and techniques. He has been instrumental in bringing Python scripting to both his government clients and the analytic workforce and has developed a 40-hour Introduction to Analytic Scripting class for that purpose. Additionally, Charles has developed a 60-hour Fundamentals of Data Science class, which he has taught to Booz Allen staff, government civilians, and US military personnel around the world. Charles has a master’s degree from Brandeis University, two bachelor’s degrees from the University of Arizona, and various IT security certifications. In his nonexistent spare time, he plays trombone, spends time with his family, and works on restoring British sports cars.

Sessions

1:15pm–1:55pm Wednesday, 09/30/2015
IoT & Real-time
Location: 3D 02/11 Level: Intermediate
Charles Givre (Deutsche Bank)
Average rating: ****.
(4.40, 5 ratings)
Many people are acquiring smart devices, and yet do not have an understanding of the data these devices gather about them and what can be done with this data if it is aggregated over time. The talk will demonstrate what data several popular devices—including the Nest Thermostat and a few others—gather and show what can be learned about an individual from this data. Read more.