Data scientists are trained to handle uncertainty. The data we work with, no matter how “big” it may be, remains a finite sample riddled with potential biases. Our models tread the fine line between being too simple to be meaningful and too complex to be trusted. Armed with methodologies to control for noise in our data, we simulate, test and validate everything we can. A great data scientist develops a healthy skepticism of their data, their methods and their conclusions.