Data Scientists work is often focused more on the research and exploration rather than the development side of building software. However, in order to demonstrate value from the analytics we do, we have to be able to deliver reliably. This often takes the form of a reproducible research report/project or a built prototype that developers/stakeholders can further experiment with. Testing is a fundamental component to any software project, though unfortunately, it can become a bit of an afterthought in the Data Science world. This talk aims to highlight why testing is so important and beneficial in a Data Scientists workflow and some pointers on how we can do more of it more often.