About me

My path into data science didn’t start in a lecture hall — it started on the production floor. Working across manufacturing operations, I learned what a Bill of Materials actually costs a business when it’s wrong, what a delayed shipment does to a customer relationship, and why “the forecast was off” is never a small sentence in a boardroom. That’s where I first understood that most operational problems aren’t people problems — they’re visibility problems.

That realization is what pulled me into data science. I wanted to build the systems that give operations and leadership teams the visibility they were missing on the floor. Today, that shows up as intelligent chatbots built on Azure OpenAI and Cognitive Services that cut resolution time for customer queries, machine learning models that predict customer churn and booking cancellations before they cost revenue, and executive dashboards in Power BI that turn raw transactional data into decisions leadership can act on in seconds. I’m not a data scientist who learned the business afterward — I’m an operations mind who picked up the tools to fix what I used to watch break.