Join Lillian Pierson, P.E. for an in-depth discussion in this video What is happening in data science globally?, part of Insights on Data Science: Lillian Pierson.
- Across the world, data science is just taking off. I was really excited to see that Facebook opened some offices in Singapore, and I looked actually today to see what the positions were that they had open and they've got several data science and analytics positions open not only in Singapore but Hong Kong, Tel Aviv, London, all over the place. As far as global organizations, there's Data Kind that's operating in Banglore and Singapore. Many of the, it's got hubs in many of the major centers around the world for doing data science charity projects, kind of like a volunteer organization, so there's a community, a whole, it's a big thriving community built up around doing data science volunteer projects, and that's exciting to me.
To bring the power of data science into the developing world where it can change, it's changing people's lives here, but we already have great lives, and to be making a difference in countries where there's real struggle, I think that's pretty amazing.
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