My Projects
check my github
Enterprise Financial Performance & Market Expansion Intelligence Platform
Enterprise Financial Performance & Market Expansion Intelligence Platform
A corporate business intelligence platform designed to guide regional investment strategies. Built on Google BigQuery, it processes massive transaction datasets and macroeconomic indicators using complex SQL window functions, delivering an executive-level Tableau storyboard that tracks customer lifetime value and market saturation.
A corporate business intelligence platform designed to guide regional investment strategies. Built on Google BigQuery, it processes massive transaction datasets and macroeconomic indicators using complex SQL window functions, delivering an executive-level Tableau storyboard that tracks customer lifetime value and market saturation.
Production-Grade Scalable ELT Pipeline for Multi-Source Financial Transaction Auditing
Production-Grade Scalable ELT Pipeline for Multi-Source Financial Transaction Auditing
An automated cloud pipeline built to ingest and unify data from legacy and modern databases into a secure Delta Lake. It leverages Databricks and PySpark for high-throughput data processing, using dbt to orchestrate optimized, low-cost data transformations and compliance audit trails.
An automated cloud pipeline built to ingest and unify data from legacy and modern databases into a secure Delta Lake. It leverages Databricks and PySpark for high-throughput data processing, using dbt to orchestrate optimized, low-cost data transformations and compliance audit trails.
Predictive B2B Churn & Revenue Optimization Engine using Explainable AI
Predictive B2B Churn & Revenue Optimization Engine using Explainable AI
A machine learning pipeline designed to predict enterprise client churn and protect high-value contracts. Utilizing an optimized XGBoost classification model in Python, the system integrates SHAP to provide clear, feature-level explanations showing account managers exactly why a corporate client is at risk.
A machine learning pipeline designed to predict enterprise client churn and protect high-value contracts. Utilizing an optimized XGBoost classification model in Python, the system integrates SHAP to provide clear, feature-level explanations showing account managers exactly why a corporate client is at risk.