Are we ready to let machines do the work so we can now concentrate on the science questions?  Have we reached the point where statistical and machine learning methods have become useful tools rather than a nuisance and the practice of the few? 
I will present four examples where significant progress has been made and the interdisciplinary practices have brought fruitful results. These include, automatic classification, Bayesian parameter inferences, event detection and anomaly detection, and design of surveys and follow ups.