Advice to aspiring data scientists: start a blog - by David Robinson
Practice analyzing data and communicating about it
If you’re hoping to be a data scientist, you’re (presumably) not one yet. A blog is your chance to practice the relevant skills.
- Data cleaning: One of the benefits of working with a variety of datasets is that you learn to take data “as it comes”, whether it’s in the form of a supplementary file from a journal article or a movie script
- Statistics: Working with unfamiliar data lets you put statistical methods into practice, and writing posts that communicate and teach concepts helps build your own understanding
- Machine learning: There’s a big difference between having used a predictive algorithm once and having used it on a variety of problems, while understanding why you’d choose one over another
- Visualization: Having an audience for your graphs encourages you to start polishing them and building your personal style
- Communication: You gain experience writing and get practice structuring a data-driven argument. This is probably the most relevant skill that blogging develops since it’s hard to practice elsewhere, and it’s an essential part of any data science career