🚀 Data Analytics & Machine Learning Portfolio (R)

📌 Project Overview

This repository showcases an end-to-end data analytics and machine learning workflow. I bridge the gap between complex data orchestration and actionable business intelligence, delivering evidence-based clarity for strategic decision-making.

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📂 Key Business Modules

1. Retail Analysis: Customer Segmentation & Churn Prediction

• 🎯 Objective: Translate raw transaction data into retention strategies.
• 💡 Achievement: Processed 500k+ records into an RFM framework and developed a Churn Prediction Model with 90.5% accuracy.
• 📊 Visualization: Executive-level Tableau dashboards serving as a "Source of Truth" for customer health metrics.

2. Big Data Pipeline: Scalable Data Orchestration

• 🎯 Objective: Process high-velocity spatiotemporal data for urban mobility insights.
• 🛠 Tech: Orchestrated a high-performance pipeline for 21.8M+ GPS records using data.table and dplyr in R.
• 📈 Impact: Derived driver activity patterns and operational mobility metrics from unstructured data.

3. Finance: Risk Intelligence & Model Benchmarking

• 🎯 Objective: Optimize credit risk assessment through algorithmic benchmarking.
• 🔬 Methodology: Compared SVM (AUC: 0.8524), Random Forest, and Naive Bayes; utilized PCA and SOM Neural Networks for dimensionality reduction.

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🛠 Tech Stack & Methodologies

• Languages: R (Advanced), SQL.
• Tools: Tableau.
• BA Frameworks: BPMN 2.0, Gap Analysis, SOA Architecture.

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Maintained by Yanhui Ma – Business Analyst & Operations Specialist