I specialize in process analysis and risk management, building the analytical tools and AI solutions that help organizations identify vulnerabilities, streamline operations, and make informed strategic decisions.
Selected work in risk mitigation, process optimization, and decision support using machine learning and applied AI.
Built a Retrieval-Augmented Generation workflow to create tailored quiz content from source materials, combining LLMs with structured retrieval for more reliable outputs.
Developed a risk-based audit framework to identify systemic anomalies in lending processes, ensuring regulatory compliance and operational consistency.
Analyzed procurement processes and supplier risk using the Kraljic model, transforming complex supply chain data into a strategic risk-management tool.
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 key drivers of employee attrition, mitigating turnover risk through targeted retention strategies and process improvements.
My work focuses on the intersection of operational risk, process analysis, and technical execution. I specialize in identifying inefficiencies and mitigating risks where technical precision and strategic clarity are both critical.
I am a specialist in process analysis and risk management, leveraging analytics, machine learning, and automation to solve complex operational challenges.
My approach centers on understanding the underlying processes of a business to identify where risk resides and how it can be mitigated—using data not just to describe what happened, but to optimize how things work.
I enjoy bridging the gap between technical analysis and practical use, turning data into a reliable foundation for operational stability and growth.