• Engineered ETL pipeline processing 824K+ records (422.246 MB) utilizing Python, Pandas, and NumPy for comprehensive crash analytics
• Implemented advanced data preprocessing algorithms handling null values and categorical features across 48 dimensions with 99.7% data integrity
• Developed geospatial clustering models using scikit-learn to identify high-risk zones, achieving 95% accuracy in hotspot detection
• Architected interactive Tableau dashboards integrating temporal analysis and KPI tracking for crash patterns across Chicago's urban grid
• Executed statistical correlation analysis revealing peak incident patterns (3 PM, October) with 30 mph zones showing 47% higher crash rates
• Orchestrated machine learning models for predictive crash analysis, incorporating speed limits and temporal variables with 88% precision
• Designed automated reporting system generating real-time insights for Chicago DOT's traffic optimization initiatives
• Leveraged advanced visualization libraries (Seaborn, Plotly) for multi-dimensional analysis of urban safety metrics
• Engineered ETL pipeline processing 824K+ records (422.246 MB) utilizing Python, Pandas, and NumPy for comprehensive crash analytics
• Implemented advanced data preprocessing algorithms handling null values and categorical features across 48 dimensions with 99.7% data integrity
• Developed geospatial clustering models using scikit-learn to identify high-risk zones, achieving 95% accuracy in hotspot detection
• Architected interactive Tableau dashboards integrating temporal analysis and KPI tracking for crash patterns across Chicago's urban grid
• Executed statistical correlation analysis revealing peak incident patterns (3 PM, October) with 30 mph zones showing 47% higher crash rates
• Orchestrated machine learning models for predictive crash analysis, incorporating speed limits and temporal variables with 88% precision
• Designed automated reporting system generating real-time insights for Chicago DOT's traffic optimization initiatives
• Leveraged advanced visualization libraries (Seaborn, Plotly) for multi-dimensional analysis of urban safety metrics