I build analytics, machine learning, and AI solutions that help organizations understand complex problems, improve operations, and make better decisions.
Selected work in machine learning, analytics, dashboards, and applied AI for decision support.
Built a Retrieval-Augmented Generation workflow to create tailored quiz content from source materials, combining LLMs with structured retrieval for more reliable outputs.
Built a data-driven review workflow to identify anomalies and patterns in lending data, enabling faster and more consistent evaluation of potential issues.
Designed an interactive dashboard to segment suppliers and categories using the Kraljic model, helping translate data into clearer sourcing decisions.
Compared traditional and transformer-based models to classify customer requests, improving how unstructured text can be routed, analyzed, and acted on.
Developed regression models to estimate property values using market, location, and property-level features, with a focus on practical model interpretation.
Analyzed workforce data to identify the drivers of employee attrition and support more targeted retention strategies.
My work sits at the intersection of analytics, machine learning, and practical decision support. I enjoy solving messy, real-world problems where technical accuracy matters, but so does clarity.
I’m a data professional with experience applying analytics, machine learning, and automation to real-world business problems.
My background includes working with complex datasets in environments where accuracy, context, and decision-making matter—but my focus is broader: building tools and insights that help organizations understand what’s happening and what to do next.
I enjoy bridging the gap between technical analysis and practical use, turning data into something that is both reliable and actionable.