Is your Masters in Computer Science? Statistics?
Is 'data science' going to be at the center of your thesis? Or a side topic?
I'll assume your in Statistics and that you want to focus your thesis on a 'data science' problem. If so, then I'm going to go against the grain and suggest that you should not start with a data set or an ML method. Instead, you should seek an interesting research problem that's poorly understood or where ML methods have not yet been proven successful, or where there are many competing ML methods but none seem better than others.
Consider this data source: Stanford Large Network Dataset Collection. While you could pick one of these data sets, make up a problem statement, and then run some list of ML methods, that approach really doesn't tell you very much about what data science is all about, and in my opinion doesn't lead to a very good Masters thesis.
Instead, you might do this: look for all the research papers that use ML on some specific category -- e.g. Collaboration networks (a.k.a. co-authorship). As you read each paper, try to find out what they were able to accomplish with each ML method and what they weren't able to address. Especially look for their suggestions for "future research".
Maybe they all use the same method, but never tried competing ML methods. Or maybe they don't adequately validate their results, or maybe there data sets are small, or maybe their research questions and hypothesis were simplistic or limited.
Most important: try to find out where this line of research is going. Why are they even bothering to do this? What is significant about it? Where and why are they encountering difficulties?