Led the design and deployment of machine learning models for user behavior prediction in XR environments, applying XGBoost and LightGBM to personalize experiences and optimize content recommendations, driving an 18% increase in user engagement. · Developed and deployed Natural Language Processing (NLP) models for automated customer support, improving response time by 25% and increasing customer satisfaction, aligning with Under Armour's customer-centric data-driven approach. · Applied time-series forecasting techniques to predict user interactions and content demand, optimizing system performanceand aligning with promotional effectiveness strategies in the retail context. · Integrated predictive models and data pipelines into production using AWS services (SageMaker, S3, ECR), ensuring scalable and efficient deployment in line with MLOps best practices. · Designed and developed data visualizations (Matplotlib, Seaborn) to deliver actionable insights to business stakeholders, enablingdata-driven decisions that enhanced operational efficiency by 20%.

· Developed and optimized predictive models for customer segmentation and price optimization, increasing marketing campaign targeting efficiency by 15%, and boosting conversion rates by 12%, using XGBoost and Bayesian statistics. · Implemented time-series forecasting for retail sales trends, reducing inventory excess by 25% and improving stock availability, driving a 10% reduction in stockouts. · Utilized unsupervised learning to analyze customer purchase patterns, leading to a 20% increase in sales by improving product assortment and pricing strategies. · Collaborated closely with marketing teams to design and analyze A/B tests for pricing and promotional campaigns, optimizingstrategies that led to a 10% increase in conversion rates and an 8% reduction in bounce rates. · Extracted and integrated data from various sources (sales, CRM, web analytics) into actionable reports, influencing senior management decisions to improve business operations and customer experiences.

Contributed to the development of predictive analytics models, including price sensitivity models, which optimized product pricing and increased profit margins. Led the data wrangling and transformation of large datasets from multiple sources, ensuring data consistency and quality formodel training and improving report generation efficiency by 30%. · Applied exploratory data analysis (EDA) and regression analysis techniques to identify trends and patterns that informed keybusiness strategies for customer acquisition and retention. · Designed and optimized SQL queries to extract and manipulate large datasets from MySQL, PostgreSQL, and MongoDB, reducing data retrieval times and enabling real-time insights. · Built and automated data pipelines, significantly reducing manual processing time and ensuring real-time data access across teamsto improve decision-making and operational agility.