Areas of Interest

Here are some of things that I have learned during my MSBA program that I am interested in working on and can bring to your company!

Machine Learning

I build machine learning models end-to-end, focusing not just on performance but on understanding how models behave and where they add real decision value. My workflow emphasizes strong baselines, thoughtful feature engineering, careful evaluation, and translating model outputs into insights that teams can actually use.

Data Analytics

I approach analytics as a process of asking better questions before building solutions. Through structured exploration, metric definition, and clear visual communication, I turn raw data into narratives that explain what is happening, why it matters, and what actions should come next.

NLP and Unstructured Data

I work with text and unstructured data to uncover patterns that traditional analysis often misses. This includes transforming language into structured signals using techniques like vectorization, embeddings, similarity analysis, and sentiment or thematic modeling to support discovery, recommendation, and insight generation.

Optimization

Optimization allows me to move beyond prediction into decision-making. I frame problems through objectives and constraints, evaluate tradeoffs, and translate model outputs into practical recommendations that balance competing goals and real-world limitations.

Data Engineering / Information Management

I build clean, reliable data foundations that make analysis repeatable and trustworthy. This includes designing structured datasets, implementing SQL-based workflows, and creating pipeline-style processes that move data from raw sources to analysis-ready systems.