I guided a friend through her career transition to being an ML engineer.
Mentoring teaches me a lot.
I recently had the opportunity to guide a friend who worked as a software engineer (SE) for two years and wants to transition to a data science (DS) role. What started as a casual chat eventually became several hours of outlining plans to become a data scientist.
Her first question was, “What should I learn new?”
Of course, I could list a dozen things in a minute, but it requires much more than a list of skills and links to popular courses. FYI, I never answered this question, neither in this post.
Some of her existing skills are invaluable to her new endeavor. She could fast-track her transition by carefully learning one. But what’s more important is thinking like a data scientist.
She doesn’t have to unlearn anything. However, some of her SE skills have little use in data science.
In this post, I summarize some of our discussions. These include which area of data science suits her interests, which new skills she needs to acquire, and how to start small and grow faster.