Data Science

Being a data scientist can have many meanings, but to me it is the convergence of four primary areas of knowledge: 

1. Programming language 

2. Data Management 

3. Research Methods 

4. Subject Matter Expertise

While there are more skills involved, without those four pillars a data scientist may struggle to produce actionable results for their given employer. Many employers themselves do not fully understand the nuances in the data world and may hire a single data scientist to do the job of an entire data team! So, being flexible and having an openness to learning new skills is also important. 

With all the different programing languages out there with varying purposes, it can be hard to navigate the which languages are the best to learn. Ultimately, I came to the realization that you need to be open to multiple languages in order to solve complex problems, especially if you don't have a team around you. With that being said, I find myself drawn primarily to R and Excel VBA. These languages have performed the most effectively in my working environment.