Why did you decide to become a mentor?
Having my own great mentors has had an extremely positive impact on me, so I personally understand the importance of a supportive mentorship. At the same time, across all my experiences as a data scientist and ML engineer, I have found that practicing servant leadership, and mentorship, for my team is among the most fulfilling ways for me to impact others. The biggest reason I mentor is the genuine enjoyment I derive from helping young talent make leaps in their own abilities. Some of my most satisfying “achievements” have been the leadership roles into which I helped to guide other data scientists and engineers, and the challenging projects I helped them to complete on their own.
How did you get your career start?
My freshman year in college, I became fascinated with computational and theoretical neuroscience. That was my earliest exposure to the idea of fitting mathematical models to complex real-world processes in a scientific framework. That fascination carried me through my undergrad degree in computational neuroscience and my PhD in neuroscience, where I worked with huge datasets of brain MRI data. It also led to all the foundations of what I do now: statistics, programming, data analysis, and scientific thinking.
That time in academia conveyed to me the power of having a great mentor. The difference between working in an environment that wants you to succeed and working somewhere that doesn’t care, cannot be overstated. I would not be where I am today without some of the great mentors that I have had over the past decade.
What do mentees usually come to you for?
Mostly I have had mentees that fall into one of two buckets:
1) Software engineers looking to transition into machine learning 2) Early career data scientists or analysts that want to understand machine learning better and become better practitioners of the art.
I focus on mentees gaining mastery of the machine learning lifecycle end-to-end. For me, this covers several core skillsets: statistical competency, programming ability, developer best practices, and communicating for impact. Depending on the mentee’s current skillset and experience, I tend to lean more heavily into one of these key areas. I value hands-on assistance and tailored guidance, adapting my instruction to meet each mentee where they are.
What’s been your favourite mentorship success story so far?
One of my favorite success stories is actually with a front-end engineer who I worked with on an AI-assisted platform for human-in-the-loop computer vision. As the technical lead on the project, I was impressed by his skills, gumption, and work ethic, but saw that much of his work was going unnoticed due to his difficulty communicating its impact to his supervisors. I, on the other hand, was convinced that he should be promoted to the lead architect for the front-end team. I worked with him over a few months to put together a presentation outlining all his achievements as well as a concrete proposal of a long-term vision for the platform’s front-end. Once the lead position opened up, we co-presented all this to the hiring managers, and he won the job! Now he is running his own team :) :)
What are you getting out of being a mentor?
You know the saying that teaching is the best way to learn. This is absolutely true in my experience as well. Teaching others is a great way to keep myself sharp. It helps me learn and stay abreast of developments in different fields of AI, and hear about applications of AI to different disciplines. And finally, I love helping others learn! It’s a great feeling when working through a difficult concept with a mentee and seeing the lightbulbs turn on when everything finally clicks.