Data Scientist

Role OverviewData Scientist to research, design, and deploy cutting-edge algorithms supporting a leading global eCommerce organization, enhancing category management, customer experience, pricing, supply chain, search, marketing, and merchandising operations across digital platforms. This role combines research, engineering, and optimization, ensuring that models not only generate insights but also scale efficiently in production.Key ResponsibilitiesDevelop demand forecasting models at traffic, SKU, and seller levels using time-series, ML, and causal inference methods.Design supply allocation algorithms to match demand signals with seller inventory, factoring in pricing, fulfillment, and WFS/3PL constraints.Build assortment demand–supply gap detection models, identifying white-space opportunities and high-return SKUs.Apply optimization & simulation (linear programming, multi-armed bandits) for inventory allocation, promotion design, and event planning.Quantify and monitor demand–supply imbalance metrics (out-of-stock loss, lost conversion, buy-box share, CTR vs availability)。Design core algorithms for recommendations, personalization, and risk detection.Develop ML models using advanced statistical methods, optimization, and deep learning.Translate prototypes into high-performance production algorithms.Build scalable AI infrastructure with MLOps pipelines, real-time serving, and model monitoring.Collaborate with product, engineering, and category teams to maximize GMV impact and seller/customer success.QualificationsStrong academic and practical foundation in machine learning, algorithms, and optimization.Proficiency in Python, C++/Java, SQL, and big-data platforms (Spark, Presto, Flink).Experience with search/recommendation algorithms, NLP, and time series forecasting.Familiarity with vector search, graph-based recommendation, and reinforcement learning.Ability to balance theory (mathematical rigor) with practical engineering (system performance).