While the field of data science continues to evolve with exciting new progress in analytical approaches and machine learning, there remain a core set of skills that are foundational for all general practitioners and specialists, especially those who want to be employable with full-stack capabilities.
Many “How to Data Science” courses and articles, including my own, tend to highlight fundamental skills like Statistics, Math, and Programming. Recently, however, I noticed through my own experiences that these fundamental skills can be hard to translate into practical skills that will make you employable.
Therefore, I wanted to create a unique list of practical skills that will make you employable.
The first four skills that I talk about are absolutely pivotal for any data scientist, regardless of what you specialize in. The following skills (5–11) are all important skills but will vary in usage depending on what you specialize in.