I can see both sides. DS is an awful lot like good-old-fashioned statistics, especially in describing the shape, patterns, and significance of events. But the rise of vast amounts of raw data of diverse kinds and origins, especially deeply contextual data like english text -- this is new, and I think it warrants a more meaningful label for the formal study and the practice of such analysis.
I also have no problem with the use of "science", since DS is one of the purest applications of the scientific method I know. You observe, you hypothesize, you explore and test, you use statistics to draw or reject a conclusion. Of course, it's almost impossible to eliminate all the confounding factors, but that's part of the fun...
The cornerstone of the scientific method is "hypothesis testing via experiments". Data scientists typically skip the experiments and make models based on pre-existing data. So, I am skeptical of calling it a science.
I also have no problem with the use of "science", since DS is one of the purest applications of the scientific method I know. You observe, you hypothesize, you explore and test, you use statistics to draw or reject a conclusion. Of course, it's almost impossible to eliminate all the confounding factors, but that's part of the fun...