I am a Data Scientist at S&P Global with close to 6 years of industry experience, including over 5 years of focused work in Data Science. A graduate of NIT Silchar, I bring a strong foundation in Statistics, Machine Learning, Optimization, and Deep Learning, along with hands-on expertise in emerging Generative AI technologies. My recent work has involved advanced applications of Retrieval-Augmented Generation (RAG), Agentic RAG architectures, and integration of frameworks such as txtai, AutoGen, LangChain, and Haystack. I have practical experience across major cloud platforms including AWS, GCP, and Azure, and am well-versed in end-to-end model lifecycle management including deployment and MLOps practices. Driven by a deep curiosity and a problem-solving mindset, I aim to deliver scalable and impactful AI solutions across industries.