I hold a Bachelor of Science in Computer Science and Economics with a Mathematical Emphasis from the University of Wisconsin–Madison, and have completed multiple certifications in Python, data science, machine learning, and SQL from institutions like IBM, the University of Michigan, and UC Berkeley. Professionally, I’ve spent over 20 years applying these skills in high-performance environments—building predictive models, data pipelines, and automation systems at hedge funds, market makers,...
I hold a Bachelor of Science in Computer Science and Economics with a Mathematical Emphasis from the University of Wisconsin–Madison, and have completed multiple certifications in Python, data science, machine learning, and SQL from institutions like IBM, the University of Michigan, and UC Berkeley. Professionally, I’ve spent over 20 years applying these skills in high-performance environments—building predictive models, data pipelines, and automation systems at hedge funds, market makers, and regulators.
While I didn’t start my career in a classroom, I’ve taught and mentored in many forms. I’ve coached junior analysts through technical interviews, led training sessions for new hires, and most recently served as a career coach with Parabolic, helping early-career professionals break into data and finance roles. I also volunteered as a tutor for First Graduate in San Francisco, supporting high school students from underrepresented backgrounds. My approach is practical and student-driven: I focus on real tools, real problems, and building confidence through clarity.
My teaching philosophy is simple—engagement and challenge. I know from experience that students learn best when the material feels relevant and just hard enough to stretch them. Whether I’m teaching Python, SQL, Excel, or machine learning, my goal is to build lasting skills that students can use in school, work, or life. I’ve worked with learners from high school to mid-career professionals, and I meet each student where they are—then push them forward.
