That’s a fundamental rule of the labor market in any industry, and data science is no exception. To read the other articles, please refer to the table of contents or the links that follow this post.) Why Data Science Projects Are CrucialĮmployers won’t pay you to do something you’ve never done before. ( This article is a part of our in-depth Data Science Career Guide. To some, the term “portfolio” evokes a carefully-designed package of projects, like a custom-built website.įor our purposes here, we’re going to define portfolio as the group of projects you’re showcasing in your job application, regardless of the format in which they’re presented (we’ll talk about presentation later in this article).īefore we dive into the how of putting together a portfolio, let’s take a look at the why. Projects often play a crucial role in the interview phase as well.įirst, a word on terminology: you’ll hear terms like projects and portfolio used differently by different people in the data science world. In fact, if you don’t have previous experience in the data science field, your portfolio of projects is probably what will determine whether you get that all-important call back for an interview. For entry-level positions, the project portfolio is where the rubber meets the road. Now we’ve reached the real meat of your job application.
Start building data science projects as early as you can. MaHow to Create a Project Portfolio for Data Science Job Applications
0 kommentar(er)
