Its not just about the science
It’s true that all data scientists need to have good analytical abilities, and expertise with the tools, languages and packages that enable them to do what they do.
There are 3 other qualities that make a great data scientist, which are not about the ‘science’ in Data Science:
- It’s not about the tools: A great data scientist knows that understanding a customer’s problem or goal is the first step towards success. Often, we’re in a rush to use the latest tools or apply this new algorithm we (finally!) understood. But a good data scientist understands that the tools and algorithms are only a means to an end – and the end is, get the customer what he/she WANTS.
- Make it explainable: The need for AI to be ‘explainable’ is being talked about more and more, but I believe it is important for data science too. A good data scientist should be able to explain to his/her customer the WHY behind a solution he/she creates. For example, if an algorithm predicts the likelihood that a customer will buy a car after visiting a dealership, the data scientist should be able to explain WHY or what factors influence the prediction.
- Continuous improvement: A great data scientist understands that no solution is the final one. Customer needs change, more data becomes available, newer/better algorithms become available. A great data scientist builds his/her solutions such that they can be improved upon without a whole lot of re-engineering.
Entrepreneur Data Evangelist