Raphael Lu

Background

About Raphael Lu

I help organizations turn complex data into actionable insights—combining machine learning, statistical modeling, and stakeholder communication to drive meaningful outcomes. With 6+ years of experience in clinical data analysis and institutional policy design, I’m now applying my analytical skill set to broader sectors including health tech, sustainability, education, and AI-driven innovation. Core Skills- Machine Learning & Predictive Modeling: Scikit-Learn, XGBoost, regression, classification, clustering - Data Engineering & Analytics: SQL, pandas, NumPy - Data Visualization & Storytelling: Seaborn, Matplotlib - Statistical Analysis & Experimental Design: Hypothesis testing, advanced statistics, IBM SPSS Key Achievements- Led a hospital-wide protocol change by synthesizing clinical studies into new ICU nutrition guidelines during early COVID-19—implemented 3 months ahead of national publications- Identified a high-risk pattern in CRRT dialysis patients, prompting a hospital formulary update that reduced trace element deficiency complications - Delivered annual lectures to clinicians, translating complex clinical research into actionable decisions at the bedside. I thrive in fast-paced, data-driven environments where problem-solving and collaboration meet technical rigor. My training at TripleTen has equipped me with hands-on experience in Python, SQL, machine learning, and data visualization, while I continue expanding my quantitative foundation through applied calculus and advanced statistics coursework. If you're looking for a data scientist or ML engineer who can bridge technical execution with strategic insight, let's connect - raphaellu.analytics@gmail.com