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

• Spearheaded the development of the 'Smart Retail Toolkit,' an advanced suite of analytics and AI-powered solutions that improved marketing and operational efficiency for retailers, generating $1M in first-year subscription revenue with a 71% renewal rate • Managed the fashion and cosmetics section (50+ merchants) of the Mall WeChat mini program, including product launch, co-branded campaigns, and loyalty program features, increasing quarterly merchant engagement by 30% and redemption rates by 25% • Reduced mall vacancy rate by 50% through earlier identification of potential store closures by optimizing KPI tracking process and developing a risk prediction model in collaboration with Leasing and Operations teams • Proactively managed ad-hoc requests, defining scopes and mitigating risks through a data-driven approach; achievements include leading a team of 12 to launch a luxury multi-brand store in 6 months and resolving a $2.5M lawsuit with Hilton Worldwide • Created comprehensive visualizations and data insights that effectively communicated product value to non-technical stakeholders

• Cut lead time by 50% and improved management engagement by optimizing reporting processes through collaboration with cross-functional teams and launching a daily leasing dashboard using Tableau and Excel • Conducted Marketing Mix Modeling (MMM) using R and Excel, evaluating online and offline media channels, identifying key sales drivers, increasing sales effectiveness by 15%, and collaborating with the internal modeling team to analyze and interpret results • Implemented Multi-Touch Attribution (MTA) using PySpark and R, cleaning and analyzing data from millions of mall consumers to optimize advertising strategies for Sephora and other clients, improving touchpoint effectiveness by an average of 20% • Identified and capitalized on revenue growth opportunities through campaign measurement and A/B testing, leveraging data from cross-shop promotions, pop-up stores transactions, and other initiatives • Designed and implemented a merchant scorecard for tenant mix optimization (shop resizing, relocating, and upgrading), contributing to effective data-driven business intelligence solutions

• Conducted financial modeling and analysis for GM’s steering business “Nexteer” bid, a $450 MM transaction, highlighted by the Wall Street Journal as a “landmark deal of the era” • Secured $500,000 in funding by presenting market insights and 3-year business plan for Global XLR, an online cross-border supply chain SaaS startup, to potential investors• Led commercial real estate portfolio research and prepared pitchbooks, integrating financial data, competitive analysis, and market insights to present compelling value propositions, securing engagement of potential investors• Executed multi-dimensional portfolio analysis using financial modeling techniques such as discounted cash flow (DCF), scenario analysis, and sensitivity analysis to evaluate investment opportunities

• Rotations in Corporate Credit Risk, Priority Banking, Client Service Group, and Trade Operations & Bank Guarantee • Developed sorting & matching algorithms for compliance screening and provided recommendations to senior management