Why She Switched from Data Scientist to Machine Learning Engineer (Mikiko Bazeley) - KNN Ep. 76
Today I had the pleasure of speaking with Mikiko Bazeley. Miki is an informally-taught Machine Learning Engineer, focused on combining 5+ years of experience in data analytics + data science, growth, & engineering to help make machine learning useful by developing tooling, infrastructure, & processes for data scientists at Mailchimp.
Prior to Mailchimp, Miki's worked as a data scientist and analyst in a number of industries like solar, 3d modeling software, anti-piracy tech, health tech and real estate tech for companies like Autodesk, Teladoc, WalkMe, etc.
In her spare time, Miki mentors, speaks, and writes about her experiences bootstrapping her learning and succeeding without a Master's or PhD. Her goal is to help shatter the myths around breaking into data science and machine learning and encourage public learning through LinkedIn.
Both Miki and I come from a mixed Caucasian and Asian homes, and we talk a lot about how finding ourselves between cultures was both liberating and alienating. She also touches on how she was able to find herself after college by truding her own path that her parents didn't quite understand. Finally we touch on how and why she transitioned from data science to machine learning engineering. This is a loaded episode as we also touched on her experience going through a data science bootcamp @Springboard .
I really enjoyed speaking with Miki and I'm excited to share this episode with you!