So you've read this book, and let's assume for the sake of argument that you thought the subject matter was pretty cool (and that the writing was brilliant, of course). What now?
My most important advice is to get out there and start tackling some real problems. I've done work as a software engineer and an academic, and I'm constantly impressed by how much more intellectually dynamic data science is than anything else I've done. In a single day, I will flit between low-level debugging, designing software architecture, helping clients to translate a business problem into math, and brushing up on my linear algebra. In data science, there is always something new that you can learn, and usually something new that you have to learn, and no book can substitute for real experience in that kind of environment.
As far as broadening your knowledge base, there are several directions (not mutually exclusive) that you might consider growing: