About Me

My Journey

My journey into Data Science started with Chubb Ltd., where I spent three years exploring data, building production ML models, and presenting findings to diverse stakeholders. Now pursing my Master of Science in Data Science at Columbia University, I’ve developed a unique perspective that bridges theoretical foundations with practical implementation. I am excited to continue growing as a professional and welcome ML opportunities with open hands!

What I Do

Production Machine Learning
At Chubb, I built and deployed Generalized Linear Models for actuarial pricing decisions, managing the complete ML lifecycle from data pipeline optimization through production deployment and governance. I facilitated our team’s transition from legacy SAS to Python, ensuring business continuity while modernizing an entire codebase.

Recommendation Systems & NLP
My recent work focuses on recommendation systems and natural language processing. In my SkinWise collaborative project, I developed a sentiment analysis pipeline that processes 581K+ product reviews to generate personalized skincare recommendations—achieving 86% accuracy and improving negative feedback detection by 46%.

Technical Expertise

Machine Learning: Supervised/Unsupervised Learning, GLMs, Ensemble Methods (Random Forest, XGBoost, Gradient Boosting)

Engineering: Production ML Pipelines, Feature Engineering, Data Preprocessing

Tools & Technologies: Python (pandas, NumPy, scikit-learn, H2O), SQL, R (ggplot2), Databricks, ADLS, Git, Jira

Education

Columbia University (Expected Dec 2026)
MS in Data Science
Completed coursework: Applied Machine Learning, Algorithms for Data Science, Probability & Statistics, Exploratory Data Analysis & Visualization

Current coursework: Statistical Inference & Modeling, Causal Inference for Data Science, Computer Systems for Data Science, Machine Learning for Data Science

La Salle University (2018-2022)
BS in Mathematics (Maxima Cum Laude)
Minors in Computer Science and Chemistry Outstanding Graduate - Mathematics Department

Beyond Work

When I’m not coding or training models, I enjoy exploring NYC’s diverse food scene, staying active through the gym, and traveling to discover new cultures. I’m fluent in English and French, conversational in Spanish, and always eager to connect with fellow ML enthusiasts.

Let’s Connect

I’m always interested in discussing ML projects, especially around recommendation systems, NLP, and production ML best practices. Feel free to reach out!

📧 ymc2123@columbia.edu
💼 LinkedIn
💻 GitHub