How to Build a Data Science Portfolio That Will Make Recruiters Swipe Right
Room: Saphire B - PyData
Time: 11:00 - 11:25
Building a strong data science portfolio can be a daunting task, especially for those just starting out in the field. In this talk, we will explore the essential elements of a successful data science portfolio, and provide actionable advice for building a portfolio that will make recruiters take notice. First, we will discuss the importance of selecting the right projects for your portfolio. We'll share tips for identifying projects that demonstrate a range of skills and showcase your expertise in a specific area. Next, we'll talk about how to present your work in a clear and compelling way, including how to structure your portfolio and which tools and platforms to use. We will also discuss how to incorporate feedback from peers and mentors, as well as how to solicit feedback from potential employers. In addition, we'll cover best practices for maintaining and updating your portfolio, and how to use your portfolio to continue learning and growing in the field of data science.
I am a seasoned data scientist with around ten years of experience in the field. I began my career as a data scientist and grew into positions as Head of Data Science and Head of Data, giving me a deep understanding of what it takes to deliver great data products. For the past five years, I have been mentoring individuals seeking to enter the data science world, and have helped guide them to success in this field.