Chapter 4 Building a Portfolio

This chapter covers:

  • How to create a data science project
  • Starting a blog
  • Example projects

You've now finished a bootcamp, a degree program, a set of online courses, or a series of data projects in your current job. Congratulations—you’re ready to get a data scientist job! Right?

Well, maybe. Part 2 of this book will be all about how to find, apply for, and get a data science position, and you can certainly start on this process now. But there's another step that can really help you be successful—building a portfolio. A portfolio is a set of data science projects that you can show to people so they can see what kind of data science work you can do.

A strong portfolio has two main parts - GitHub repositories, or repos for short, and a blog. Your GitHub repo hosts the code for a project, and the blog shows off your communication skills and the non-code part of your data science work. Most people don’t want to read through thousands of lines of code (your repo); they want a quick explanation of what you did and why it’s important (your blog). And who knows, you might even get data scientists from around the world reading your blog, depending on the topic. As we'll cover in the second part of this chapter, you don't just have to blog about analyses you did or models you built; you could explain a statistical technique, write a tutorial for a text analysis method, or even share career advice, like how you picked your degree program.

4.1      Creating a project

4.1.1   Finding the data and asking a question

4.1.2   Choosing a direction

4.1.3   Filling out a GitHub README

4.2      Starting a Blog

4.2.1   Potential topics

4.2.2   Logistics

4.3      Example Projects

4.3.1   Data science freelancers – a project by Emily Robinson

4.3.2   Training a neural network on offensive license plates – a project by Jacqueline Nolis

4.4      Interview with David Robinson, Data Insights Engineering Manager at Flatiron Health

4.4.1   How did you start blogging?

4.4.2   Are there any specific opportunities you have gotten from public work?

4.4.3   Are there people you think would especially benefit from doing public work?

4.4.4   How has your view on the value of public work changed over time?

4.4.5   How do you come up with ideas for your data analysis posts?

4.4.6   What’s your final piece of advice for aspiring and junior data scientists?

4.5      Summary