A comprehensive collection of data science and machine learning projects showcasing the intersection of technical expertise and business impact.
Built ML model predicting customer churn with 89% accuracy, leading to 23% reduction in churn rate and $2.4M ARR retention through targeted interventions.
Engineered automated financial data pipeline integrating EODHD API to analyze $1.2T+ S&P 500 ETF performance, calculating risk-adjusted returns and revealing 8.5% performance differential between weighting strategies. Applied quantitative analytics methods with real-time processing of 231 trading days, volatility modeling, and portfolio optimization insights for institutional investment decisions.
Developed sentiment analysis API for customer feedback with 92% accuracy, enabling real-time prioritization of critical issues and improving CSAT scores by 18%.
Built production-ready ML pipeline processing 300K+ NBA game records with automated web scraping, K-means clustering, and PCA analysis to identify team performance patterns and championship-winning strategies. Implemented scalable data engineering system with checkpoint recovery, statistical validation, and automated feature engineering for multi-dimensional sports analytics.
Processed 4.7M+ arrest records from NYPD/LAPD datasets with advanced statistical analysis, temporal pattern recognition, and geospatial density mapping to identify population-crime correlations. Developed automated analytics pipeline delivering stakeholder-ready insights for urban planning and resource allocation through data standardization and visualization techniques.
Developed collaborative filtering recommendation system that increased average order value by 28% and improved cross-sell conversion by 34%.
Designed and executed A/B test on pricing strategy, identifying optimal price points that increased revenue by 16% without impacting conversion rates.
Implemented NLP-based automatic ticket routing system using topic modeling, reducing average resolution time by 31% and improving customer satisfaction scores.
Built time series forecasting model predicting product demand with 91% accuracy, optimizing inventory management and reducing stockouts by 45%.
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I'm always excited to tackle new challenges and create data-driven solutions that deliver real business value.