Join Lillian Pierson, P.E. for an in-depth discussion in this video What best practices do you recommend for landing a great job in data science?, part of Insights on Data Science: Lillian Pierson.
- To me, the easiest, best way to get a job is just to start doing and to create a website and put your projects, maybe make some hobby projects, and put them on the internet. And just start putting your stuff out there, and show what you can do. And explain how this can help people, and that's going to bring the opportunity to you. But going and looking for jobs and competing against, you know, a few hundred other people, I don't know, I think in this day and age, that's not the way to go. It's better just to start doing what you want to do and let the stuff come to you.
I found that was pivotal for me because I wasn't much into social media and being anywhere public, and then I found out that that's actually a big part of careers these days, is that you're, have a public presence in what you do and are willing to stand behind it.
Lillian began her career not as a data scientist, but as an environmental engineer. Here, she shares her story, discussing how she taught herself to code in Python and R, and work with data science methodologies. As a result of her own experiences, Lillian is passionate about helping those interested in data science—but who may lack a four-year degree in the discipline—get started in the field. She shares practical ways to acquire the skills and experience needed to become a data scientist, and best practices for landing a job. Lillian also dives into grappling with the challenges that occur in rapidly evolving tech workforces. Plus, she discusses the industry itself, covering recent changes in the field and areas of need, and clearing up a few common misconceptions.
- Practical ways to acquire data science skills and experience
- Which courses should you take to become a data scientist?
- What challenges should people be prepared to encounter?
- Best practices for landing a job in data science
- Common misconceptions
- What key personality traits are common among successful data scientists?
- How has the industry changed in recent years?
- Practical advice for minorities and women pursuing a career in data science