Join Lillian Pierson, P.E. for an in-depth discussion in this video How has the industry changed in recent years?, part of Insights on Data Science: Lillian Pierson.
- When I started in data science, it was getting a lot of visibility. So there was a time when companies were just going on hiring sprees and hiring tons of data scientists everywhere. As far as the changes I've seen in the industry since, say, 2011 or 2012 is that, well, it's moving fast. As the industry develops, the expectation of the data scientist also advances. Moving into the upcoming future with IoT analytics, there's going to be a really heavy demand for data scientists who know how to work with IoT technologies.
In the beginning it was more of a thing that benefited Amazon, Facebook, Google, but now because of cost feasibility, even smaller mom and pop shops are able to benefit from big data and data science insights. I also think that the focus has kind of changed. So, yes, it's about business value, either by making more sales or capturing lost costs, but with the IoT it's now becoming about how is this affecting people in their lives, in their home, when they're at the gym? This is really making an impact on people's lives outside of business.
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