Data Scientist (Student Team) - Dell Capstone - Outbound Freight Optimization
Innovatively developed and executed a freight pricing analysis system at Dell, utilizing machine learning and predictive analytics. This system streamlined competitor pricing analysis and played a pivotal role in reducing freight costs by 50%, enhancing both cost-efficiency and market responsiveness in a dynamic environment.• Developed an optimization model for shipping rates, and deployed Time Series and Machine Learning Models to predict demand and customer choices, achieving $4M+ in projected annual savings and a 28% increase in delivery value • Designed and executed a survey with 5,000+ responses, using conjoint analysis to address dataset granularity issues, providing detailed insights into customer preferences and sensitivity to shipping rates for more accurate and targeted decision-making • Created and streamlined new performance metrics cross-functionally to align with Dell’s strategic supply chain goals in US, effectively balancing customer experience, logistics profitability, and working capital as a cohesive portfolio • Automated ETL pipeline with Data Engineering and Operations teams, enhancing data accuracy by 15% and reducing processing time by 80%; conducted root-cause analysis and scenario planning to refine the optimization strategy and improve model accuracy • Built interactive dashboards with Tableau and advanced data visualization techniques to generate and present actionable insights