In this talk, I will weave together a personal data story, how it led me to be an advocate for the importance of mentoring others, and why mentoring matters for healthy, inclusive, and productive communities.

Through looking at data, both quantitative and qualitative, I'll draw some life conclusions from the data. Some of these conclusions will fall prey to the failures of bias, small sample size, and inadequate data cleaning. From these data failures, I'll share valuable lessons which shaped my five keys of "high impact" mentoring:

• Show up
• Listen
• Question
• Act
• Recharge

We'll wrap up with a critical look at how mentoring benefits you personally while also bringing more humanity to our data science community and the important work we do.