Proven leader in predictive ecommerce analytics and performance-driven digital marketing optimization. Specialist in transforming complex data into revenue-generating forecasts and campaign strategies that deliver measurable ROI across enterprise retail operations.
Advanced predictive modeling for revenue, inventory, and demand forecasting across 200K+ SKU catalogs with proven multi-million dollar impact
Expert in attribution modeling, campaign optimization, and media mix analysis driving exponential audience reach and ROAS improvement
Advanced attribution modeling and journey analytics across 800+ store locations with proven ROI optimization
Expert in cloud-based data architectures using Python, R, and modern BI tools for maximum analytical efficiency
Architected comprehensive revenue forecasting system that accurately predicts annual revenue outcomes and enables real-time strategy adjustments. Built dynamic models processing massive ecommerce datasets to deliver precise KPI forecasts.
Developed sophisticated Python-based forecasting algorithms incorporating seasonality, promotional impacts, and market trends. Created automated adjustment mechanisms for period-by-period optimization. Integrated machine learning models for demand prediction across 200K+ SKU inventory.
Led deployment of sophisticated digital marketing attribution system transforming media spend optimization across TV, DSP, and search channels. Eliminated agency bias and dramatically improved ROAS through internal attribution mechanisms.
Built custom multi-touch attribution models using location data and customer journey analytics. Integrated Adobe Ad Cloud DSP with advanced geospatial targeting. Developed real-time campaign optimization dashboards enabling exponential audience reach expansion and strategic budget reallocation.
Developed sophisticated customer journey mapping system using advanced analytics tools and AI to identify pain points, optimize touchpoints, and predict customer behavior across digital channels.
Leveraged ContentSquare, FullStory, and custom Python models to analyze customer interactions. Built predictive models for customer lifetime value and churn prediction. Created automated alert systems for journey optimization opportunities.
Built comprehensive KPI forecasting system that mines massive data lakes using AI and advanced statistical models to predict annual revenue outcomes and adjust strategies in real-time.
Developed Python-based data mining algorithms that process terabytes of transaction data. Created dynamic forecasting models that adjust based on seasonal trends, marketing campaigns, and external factors. Integrated with Google Cloud for scalable processing.