Geometry and Topology are often (mis)taken as pure unapplied parts of Mathematics. With the data science artificial intelligence revolution this false assumption has been shattered once more. In this talk I present two examples of how a geometer can contribute to the growing field of data science, I show how discrete geometry of finite sets of points can be used to understand statistical inference methods such as logistic regression and how basic homology of simplicial complexes plays a role in clustering data and image processing. But perhaps even more surprising, I will show with one example that data science and artificial intelligence may also help mathematical areas such as algebra. The new results I will discuss are joint work I wrote...