Bio

I adore measurement, teaching machines how to make decisions, making the complex as simple as possible but no simpler, strategy, and creating. For organizations of all sizes and types (business, government, non-profit), I support the foundation of an organization's strategy by exploring data in order to identify valuable opportunities and potential challenges, designing experiments to inform guiding policies, and crafting machine learning solutions to drive coherent action. Let's use science to become even better. I've included some favorite resources for new and aspiring data scientists: • http://norvig.com/experiment-design.html • http://norvig.com/21-days.html • http://www.unofficialgoogledatascience.com/2016/10/practical-advice-for-analysis-of-large.html • https://amstat.tandfonline.com/doi/full/10.1080/00031305.2016.1154108 • http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/ • https://blog.ycombinator.com/learning-math-for-machine-learning/ • https://www.codewars.com/ • https://arxiv.org • The Pleasure of Finding Things Out by Richard Feynman • How to Lie with Statistics by Darrell Huff • Good Strategy Bad Strategy by Richard Rumelt • Thinking in Systems by Donella Meadows