At Airbnb, I led global customer contact forecasting systems across multi-language, multi-channel environments, supporting 35+ contact centers. I designed and deployed time series models that improved forecast accuracy from approximately 15–20% error to 3–5%.
Those forecasting improvements delivered $30M–$45M in annual cost savings through better workforce planning and operational efficiency. I also automated forecasting pipelines, reducing cycle time by five working days.
At Huawei, I developed performance dashboards for App Gallery and in-app purchases, and delivered insights on user acquisition, retention, and revenue optimization. My work also includes pricing and promotion analysis at Dunnhumby, marketing analytics and A/B testing at Groupon, and academic teaching and research in physics.
