Hari haran Suresh kumar

I’m an M.S. in Data Science graduate from the University of Washington, with hands-on experience building and validating ML models, running experiments, and translating complex findings into actionable business insights. I’m proficient in Python, SQL, PySpark, and AWS across healthcare and financial domains, and I actively use AI tools across the SDLC to accelerate delivery and improve code quality.

At Virginia Mason Franciscan Healthcare, I built an end-to-end ML pipeline on 275 patient records using Ridge Regression, XGBoost, and Random Forest to predict postoperative shifts across spinal alignment parameters—replacing a manual measurement process. I also engineered a genetic algorithm optimization framework using PyMoo to evaluate 1000+ candidate surgical plans per patient across multiple generations, and I collaborated with 9 surgeons to validate outputs using SHAP plots and confusion matrices.

Previously, at US Bank, I worked as an Analyst Trainee and Cognizant India Analyst, optimizing SQL queries to reduce processing time by 30% and improving data modeling with star schema design, SQL views, and documentation used by 200+ users. I also build practical projects like an AWS serverless ETL pipeline and an interactive Tableau dashboard, and I enjoy partnering across engineering and domain experts to ship measurable, reliable results.