• Developed ML models in R to predict PayScale and job demand based on student majors, improving prediction accuracy by 15%.• Created an ML pipeline for a multilabel text classifier to categorize UTD Restaurant reviews. Conducted EDA, requirements gathering, and sentiment analysis using Python NLTK and Spacy.• Designed and led end-to-end analytics and ML optimization sessions on the developed models, increasing process efficiency by 20%.

- Performed in-depth data mining and developed custom ad-hoc business reports and dashboards using Tableau and Excel, enabling the real-time tracking of key sales metrics across the Asian market.- Analyzed complex sales datasets to identify actionable insights, which led to a 15% improvement in sales strategy effectiveness by refining market approaches and optimizing product positioning.- Delivered clear, data-driven insights and strategic recommendations to executive leadership, fostering informed decision-making processes that resulted in a 10% increase in overall process efficiency.- Collaborated with cross-functional teams to drive continuous improvement initiatives and streamline reporting workflows, aligning operational processes with business objectives.

Enterprise Data Science Platform (EDSP)- Collaborated with cross-functional teams to design, develop, and rigorously test an innovative platform that integrates Machine Learning (ML), Business Intelligence, data analytics, and AWS cloud services. The platform reduced data processing time by 30%, significantly improving operational efficiency.- Enhanced platform capabilities by incorporating advanced analytics features and leveraging emerging technologies, which resulted in a 25% increase in user satisfaction based on stakeholder feedback.- Constructed and validated a wide range of machine learning models, including regression, classification, clustering, natural language processing (NLP), time series forecasting, and geospatial analysis. This resulted in an overall improvement of up to 15% in model accuracy and prediction performance.- Authored comprehensive documentation for AI/ML and analytical tasks, providing clear guidelines that improved team productivity by 10%.Driving Video Analysis- Leveraged ML techniques to analyze employee driving videos, extracting critical performance indicators, and improving the accuracy of consumer driving behavior analysis by 20%.- Designed and implemented a face mask detection model using Convolutional Neural Networks (CNN), achieving a remarkable accuracy rate of 95.7%.Gamma Data Quality Enhancement- Implemented regression models to predict automotive battery capacities and speeds, contributing to a 5% increase in data quality.- Developed and deployed an anomaly detection app, leading to a 2% improvement in overall data quality.Visual Inspection (R&D)- Developed CNN, LSTM, GRU, and YOLO models using Python to identify defects on engine surfaces, enhancing defect detection accuracy by 18%.