Machine Learning & Data Science Projects

Explore my recent data science and machine learning projects, ranging from event-driven ML pipelines to unsupervised learning and interactive visualizations.

Event-Driven ML Pipeline with Vertex AI and Gemini for Call Transcript Classification

Event-Driven Call Transcript Classification Pipeline with Vertex AI and Gemini

Developed a real-time machine learning pipeline for processing and classifying call center transcripts for CDP activation. This solution leverages GCP's event architecture for seamless processing, Vertex AI pipelines, and Gemini LLMs for classification.

Vertex AILLMsGeminiKubeFlowGCP
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Customer Segmentation Pipeline with K-Means for Sports Streaming Platform

Customer Segmentation Pipeline and Advanced Feature Engineering for a Sports Streaming Service

Developed a customer segmentation pipeline for a large sports streaming brand using K-means clustering and sophisticated feature engineering. The solution identified distinct viewer personas based on viewing patterns, engagement metrics, and content preferences, enabling targeted marketing campaigns.

PythonScikit-learnK-MeansVertex AI
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Media Mix Modeling Visualization Placeholder

Maximizing Marketing Effectiveness with Media Mix Modeling for a Home Services Leader

Used Meta's Robyn and custom data pipelines to uncover ROI-driving media channels, reduce inefficient TV spend, and improve lead volume by 44% YoY in optimized markets. This project delivered actionable insights that transformed the client's marketing strategy.

RRobyn (Meta)ProphetTime SeriesMarketing Analytics
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Explore my interactive Tableau dashboards that transform complex data into actionable insights through intuitive visualizations.

Discover more of my data visualization work on Tableau Public