Why did you decide to become a mentor?
Throughout my career in senior data science roles and management, I realized that helping colleagues and direct reports untangle their technical and career hurdles was easily the most rewarding part of my job. That drive to support others naturally pushed me to expand my mentorship outside the traditional corporate structure. Having made the transition into tech from an academic research background myself, I know firsthand how intimidating and opaque the industry can feel from the outside. I want to give people the straightforward guidance, technical clarity, and honest feedback I wish I had when I was first making my way through the tech world.
How did you get your career start?
My journey began during my time as a postdoctoral astrophysics researcher at UC Santa Cruz. In academia, I spent years writing Python code to run complex machine learning simulations, building computational models long before "data science" became a mainstream industry buzzword. While working in Northern California, I started networking with peers transitioning into the private sector and attending tech meetups across the Bay Area. Seeing how naturally my research background translated to solving real-world business challenges inspired me to make the pivot into industry, and I’ve been building production-level AI and data systems ever since.
What do mentees usually come to you for?
Mentees usually reach out when they're facing a pivotal transition point in their career and need a practical roadmap. Many are academics looking to translate their research experience into industry-ready data science roles, or professionals in non-technical functions like product, support, or design trying to pivot into data analytics. I also work extensively with experienced data scientists who feel stuck, whether that’s struggling to break through from senior to staff level, making the deliberate transition from management back to an individual contributor role, or trying to pass high-stakes behavioral and technical interviews at top-tier tech companies.
What's been your favourite mentorship success story so far?
One of my favorite experiences was working with a researcher who had spent years in her PhD and postdoc doing heavy data analysis, but couldn't seem to break through in industry job applications. She was already doing the work of a data scientist daily, but her resume was framed around academic rigor rather than business impact. We worked together to completely overhaul her resume to speak the language hiring managers look for, and then focused heavily on behavioral interviews, which is often where candidates struggle most to sell their story effectively. Watching her land her first industry role and seeing how much happier and confident she became made the entire process incredibly rewarding.
What are you getting out of being a mentor?
Mentoring keeps me grounded and sharpens my own leadership skills every single day. Working with people from diverse backgrounds forces me to look at data science problems with fresh eyes, challenge my own assumptions, and refine how I communicate complex ideas clearly. There is immense personal satisfaction in helping someone clear a hurdle that has been keeping them up at night, whether that's debugging a technical pipeline approach or walking into a job interview knowing exactly how to articulate their worth. It reinforces why I fell in love with this field in the first place.
