At Michigan Technological University, I build Python data pipelines for quantitative research and develop regression, classification, and forecasting models to analyze market behavior. I also engineer financial indicators and time-series features, applying PCA to examine market trends, volatility, and risk.
At Concentrix, I improved ticket resolution accuracy by 15% through quality audits and a standardized scoring rubric, and reduced repeat-contact escalations by 10% by analyzing ticket trends. My projects include a reproducible MLOps pipeline for hospital readmission prediction and a retinal image classifier that achieved 84.4% accuracy with ResNet50.
