I am a Data Scientist and Machine Learning Engineer with a strong background in predictive analytics, Generative AI, and production-grade machine learning systems. I hold a Master of Applied Science in Mechanical Engineering from the University of Windsor, where my research focused on computational modelling, fluid dynamics, and machine learning applications. Over the years, I have built and deployed end-to-end AI and analytics solutions across customer intelligence, forecasting, anomaly detection, sentiment analysis, and business automation. My work spans traditional machine learning, statistical modeling, Retrieval-Augmented Generation (RAG), LLM orchestration, and agentic AI systems using tools such as Python, SQL, Snowflake, Databricks, LangChain, LangGraph, FastAPI, and cloud platforms like AWS and GCP. I have developed churn prediction models, customer lifetime value forecasting systems, CRM analytics pipelines, and AI-powered assistants that transformed complex structured and unstructured data into actionable business insights. One of my most notable projects was a production-grade RAG-based AI assistant for a restaurant business, designed to automate customer support by retrieving grounded information from operational documents, significantly reducing repetitive support workload and improving response speed. What makes me stand out is my ability to bridge technical depth with business value. I do not just build models, I design scalable AI systems, optimize workflows, monitor performance, and translate ambiguous business challenges into measurable solutions. My experience spans analytics, intelligent automation, LLM applications, and enterprise AI systems, with a strong focus on reliability, governance, and practical impact.…I am a Data Scientist and Machine Learning Engineer with a strong background in predictive analytics, Generative AI, and production-grade machine learning systems. I hold a Master of Applied Science in Mechanical Engineering from the University of Windsor, where my research focused on computational modelling, fluid dynamics, and machine learning applications. Over the years, I have built and deployed end-to-end AI and analytics solutions across customer intelligence, forecasting, anomaly detection, sentiment analysis, and business automation. My work spans traditional machine learning, statistical modeling, Retrieval-Augmented Generation (RAG), LLM orchestration, and agentic AI systems using tools such as Python, SQL, Snowflake, Databricks, LangChain, LangGraph, FastAPI, and cloud platforms like AWS and GCP. I have developed churn prediction models, customer lifetime value forecasting systems, CRM analytics pipelines, and AI-powered assistants that transformed complex structured and unstructured data into actionable business insights. One of my most notable projects was a production-grade RAG-based AI assistant for a restaurant business, designed to automate customer support by retrieving grounded information from operational documents, significantly reducing repetitive support workload and improving response speed. What makes me stand out is my ability to bridge technical depth with business value. I do not just build models, I design scalable AI systems, optimize workflows, monitor performance, and translate ambiguous business challenges into measurable solutions. My experience spans analytics, intelligent automation, LLM applications, and enterprise AI systems, with a strong focus on reliability, governance, and practical impact.WWWW…