My Journey in Tech and Beyond
I started programming when I was around 13, building basic CRUD applications with Java, Ruby on Rails, and PHP just to see how things worked. But my real introduction to data came during my undergrad in Mathematics. I wanted to apply what I was learning, so I picked up R and MATLAB. During an internship for a high-end cycling store, I used R for social media comment mining to identify community influencers and run targeted promotions.
My first official role at Crayon Data was actually an internship in sales and marketing, focusing on lead generation. But I couldn't help myself—I picked up Python just to automate the repetitive parts of the job. The transition to data felt inevitable after that. I wanted to understand how hundreds of millions of transactions were analyzed and how human preferences were mined. Given the opportunity to join as a junior data scientist, I ran campaigns based on the company's recommender system, but curiosity got the better of me again. I started picking up more machine learning, building churn prediction and propensity models to augment the recommendation engine.
If those early experiences taught me one thing, it's this: just start somewhere. Even if it's not perfect, start doing and the rest will unravel. Don't freeze in analysis. That mindset enabled me to approach everything with curiosity and a focus on growth—asking what I can learn and how I can solve the problem faster.
Moving to Leadership
Eventually, I reached a fork in the road: take a senior data science role, or step into product management. By that point, I was effectively a full-stack product developer. I could build data engineering pipelines scaling to 500 million monthly records on Spark and Hadoop, deploy data science models, handle MLOps, write REST APIs, and wire up basic frontends.
But I realized I wanted to understand why certain things were built, not just how. I became deeply interested in the business and the user—the actual value associated with our work. I wanted to solve the user's problems, not just the technical ones. That pulled me fully into product management, and eventually into my current role as a Director of Product, where I lead teams to build agentic AI systems for the enterprise.
Beyond Work
I am an avid reader and deeply interested in history—I believe patterns repeat over time, and studying what has happened fascinates me. I also love photography and occasionally write.
Most importantly, I love solving problems that matter. I actively advise non-profits, helping them solve operational bottlenecks with technology so they can scale their impact.
My Working Style Profile
- Myers-Briggs (INTP): Analytical, curious, and driven by a need to understand how complex systems work.
- StrengthsFinder: Learner, Achiever, Arranger, Competition, Ideation.
Built models for big banks; my customer-profile project tripled how often our recommendations led to a sale.
Ran the recommendations platform and delivered 28 models for five to six banks in six months.
Built a data platform from scratch and shipped AI for a payments app, a marketplace, and a global retailer — and scaled a recommender to 60 million people.
Own a product line and its budget, launched three live AI products, and lead 3 product managers and 20+ engineers.
Big banks, a national payments app, and a card company with 60 million users — models and recommendations that help them serve customers better.
An online marketplace and AI shopping assistants that help people find what they want and buy it.
An AI travel assistant, work with a global airline, and AI features for large CPG and retail brands.
A data platform built from scratch, plus AI agents — including one that turns plain-English questions into database answers, ranked in the world's top 40.
Tools that handle invoices and write proposals automatically — turning jobs that took days into ones that take minutes.