Data Analytics

From early in my career, I discovered a deep satisfaction in making sense of complex information. While many people see spreadsheets, datasets, and code as intimidating, I see them as a puzzle — a challenge to be solved and a story waiting to be uncovered. Over the years, this curiosity has become a professional calling. As an economist with over a decade of experience, and as someone who holds a Doctorate in Business with a focus on econometrics and forecasting, I’ve developed a passion for using data to answer meaningful questions, support better decisions, and drive strategic outcomes.

One of the things I enjoy most about data and business analytics is writing code to bring raw information to life. Whether I’m using SAS to clean and transform large datasets or applying queries to organize and structure complex inputs, the process of coding is both creative and logical. I find energy in debugging a script, refining a statistical model, or building out a program that flags anomalies or trends. Programming allows me to interact directly with data — to shape it, test it, and draw it into clearer focus. There's a certain art to making messy data usable and transforming it into insight that others can act on.

But perhaps what I enjoy most is the interpretation — the moment when a statistical model starts to reveal something meaningful. Whether it's a regression model forecasting future trends, a correlation analysis identifying hidden relationships, or a time-series model tracking economic behavior, these tools help us move from guessing to knowing. That’s where data analytics truly shines — not in the math alone, but in the clarity and direction it provides. For me, analytics isn’t just about numbers; it’s about discovery, communication, and using knowledge to make a difference.