If you do a Google search for how to become a data scientist, you’ll likely be confronted with a laundry list of skills, from statistical modeling to programming in Python through communicating effectively and making presentations. One job description might describe a role that’s close to a statistician’s, whereas another employer is looking for someone who has a master’s degree in computer science. When you look for ways to gain those skills, you’ll find options ranging from going back to school for a master’s degree to doing a bootcamp to starting to do data analysis in your current job. Put together, all these combinations of paths can feel insurmountable, especially to people who aren’t yet certain that they even want to be data scientists.
The good news is that there isn’t a single data scientist who has all these skills. Data scientists share a foundation of knowledge, but they each have their own specialties, to the point that many couldn’t swap jobs. The first part of this book is designed to help you understand what all these types of data scientists are and how to make the best decisions to start your career. By the end of this part, you should be prepared with the skills and understanding to start your job search.