These four recommendations can help prepare you -- or the novice analyst on your team -- for a career in this burgeoning field. When Aurora Peddycord-Liu started as an analytical education intern at SAS in the summer of 2017, she came with a solid educational background from Worcester Polytechnic Institute and NC State's computer science Ph.D. program. These programs prepared her well for her current position at SAS, where she uses data to derive actionable insights on the design and use of SAS e-learning courses, but she's had to adapt her skill set to face the challenges of a real-world analytics position. To learn how newbie analysts can prepare for their work in this hot new age of machine learning, I spoke with Peddycord-Liu and senior executive, Dan Olley, global CTO at Elsevier. Recommendation #1: Don't be overwhelmed -- just get started Don't be intimidated by the powerful tools at your disposal; find a point to start and dive in.