Expertly crafted and optimized large datasets derived from comprehensive customer feedback, including diverse metrics, leveraging ML techniques and algorithms for notable clients like Taco John's. Monitored and maintained automated workflows for VIN decoding, ensuring accurate integration of client-provided data into production databases. Optimized stored procedures, implemented validation rules, and enhanced error handling to support evolving business requirements. Conducted sentiment analysis, entity recognition, and theme extraction using Lexalytics NLP to drive data-driven decision-making. Leveraged InMoment's CXIC platform to extract, analyze,visualize customer experience data, transforming raw data into actionable insights to drive strategic initiatives. Executed comprehensive feature engineering processes using Python, enhancing data quality and ensuring robust input for predictive models. Utilized machine learning frameworks like Scikit-learn and TensorFlow to train and optimize models, achieving high accuracy in predicting customer satisfaction and churn. Applied statistical techniques, including regression analysis, classification, and clustering, to uncover patterns within customer feedback and collaborated with cross-functional teams to integrate these insights into marketing, product development, and customer service strategies, leading to measurable improvements in customer engagement and retention.

I gained comprehensive hands-on experience in .NET and web development technologies. I worked closely with cross-functional teams to design, develop, and implement scalable web applications Developed and maintained backend services using ASP.NET MVC, Entity Framework, and C#, enhancing the efficiency of internal tools and client-facing applications Identified and resolved critical issues in production systems, reducing bug occurrences by 20% and improving system reliability.