A panel discussion on the landscape of data science with a variety of data science practitioners to add their experience and perspective.

Topics & Questions to be addressed:

• The most interesting case studies of applied analytics that our panelists have been involved with

• Is it all going to be machine learning, AI, and coding?

• Does the data have to be big? and what is "big data" anyway?

• What background is most suitable for data science?

• What is the need for statisticians? mathematicians? computer scientists?

• How essential are skills in SAS, SPSS, python, and r ?

• What are the new “must have” skills?

• Is a graduate degree a must?

• Are data science bootcamps replacing graduate degrees to get people into the field quickly?

• How is data science different than data mining? business intelligence? analytics?

• How does/should data science fit into an organization?

We will also hear from our panelists their advice for those considering a career in the field.

Panelists

Neil Bartlett, SVP Enterprise Information Management at RBC

Ceni Babaoglu, Senior Data Analytics Associate at Ryerson University

Emma Warrillow, Chief DiGGer, Data Insight Group Inc.

Ozge Yeloglu, Chief Data Scientist, Customer Success Unit at Microsoft Canada

Sarah Siu, Business Intelligence, Shopify