A Quick Data Science Project Tip! #SHORTS
You don’t need to do a completely novel analysis or use brand new data to differentiate your projects. Sometimes, a great story will do as much or more than these to get you noticed.
Rather think jumping straight into an analysis, think about who the analysis is for. Working with the titanic dataset has completely new meaning if you are analyzing it to understand risk for an insurance company looking to cover another large ship. An analysis of the iris dataset comes to life if your customer is the largest flower shop in new York trying to reduce costs by identifying pickable flowers with machine learning. These are the most boring and common projects you can do, but they have become exciting by envisioning the customer and the story associated with them.
If you want to stand out, add these elements to your projects and talk about them in story form on your resume and in your interviews. This was a short video, so do me a favor and watch it again. While you’re watching, think about who the target of your most recent project is and how you could tell a great story about it.