👋 Hello!
I'm Mia, a Technical Product Manager and Georgia Tech CS grad student who enjoys problem solving by building products people love. My work spans mobile app, AI products, and ML infrastructure. I'm equally comfortable in a data notebook and a product roadmap.
I'm a Technical Product Manager with 7+ years shipping products that people actually use. I started as a PM analyst, grew into leading mobile app strategy, and scaled a mobile product to 3M+ daily active users and $1B in revenue at Cigna.
More recently, I pivoted into AI and ML infrastructure. I spent time owning an end-to-end AI decision intelligence platform, and I'm now moving into platform PM work, building the feature store and ML infrastructure that powers models at scale. It's a different kind of problem: less about user-facing polish, more about reliability and developer experience.
I'm also in my Georgia Tech MSCS, going deeper on algorithms and systems.
I think the best PMs are technically savvy, honest with data, and deeply care about the people using what they build.
ML is only as valuable as the product decisions it informs. I build and ship both sides: the models and the products that put them to work.
Built a LangGraph multi-agent chatbot with AWS Bedrock (Claude Sonnet 4) that answers natural language questions about investment portfolios. Holdings, ETF look-through exposure, performance vs benchmarks, all via natural conversation.
Currently building the feature store and ML platform infrastructure that helps data scientists move faster and ship more reliably. Previously owned an AI decision intelligence platform that processed sales engagement signals for advisor and leadership workflows.
End-to-end ML pipelines covering EDA, feature engineering, model selection, and evaluation, applied to house price forecasting, survival prediction, and trading signal analysis.
A selection of side projects, built out of curiosity, outside of work.
You don't need to be a 10x engineer. But understanding what's hard, what's easy, and what's impossible changes every conversation with your team.
Building a trading simulator was an exercise in humility, and a crash course in how much noise exists in data we assume is meaningful.
How introducing data-driven experiments at Cigna changed how we thought about product decisions, and why most A/B tests are set up to fail.
Whether you're hiring, collaborating, or just want to talk product, ML, or multi-agent systems, I'd love to hear from you.