Thomas Speidel
data scientist and statistician in Calgary, Alberta, Canada
I'm a Statistician and Statistical Data Scientist. I apply statistical methods to solve problems throughout the organization. Previously, I worked as a Statistician in cancer research.
I am passionate about statistics, evidence based methods and communication of results. Communicating results in data science means making abundant use of visualizations and utilizing words and measures that avoid distorting or creating misleading perceptions. I'm particularly interested in decision making under uncertainty and communicating risk for optimal decision making.
When I'm not working I'm busy chasing three kids around the house, skiing, cooking, and getting up mighty early to take landscape pictures.
Inspiring Statisticians: Frank Harrell, Andrew Gelman, Douglas Altman, Sander Greenland, David Spiegelhalter, Edward Tufte.
Recent non-technical books I enjoyed: Daniel Kahneman, "Thinking Fast and Slow"; Phil Rosenzweig "The Halo Effect"; Green and Gabor "Misleading Indicators"; Goldacre "Bad Science".
Podcasts I listen to: Data Stories; Informs Analytics Podcast; Talking Machines; The Data Skeptic Podcast; Partially Derivative; O'Reilly Data Show; The Linux Action Show; Not So Standard Derivative; Linear Digressions.