Data Scientist with comprehensive experience in crafting and executing AI/ML-powered, domain-specific, and data-driven solutions with Advanced Analytics integrations. Currently focused on addressing business challenges and conducting extensive Research and Development in the realm of Generative AI, including LLMs, Fine-Tuning LLMs, Prompt Engineering, Retrieval Augmented Generation (RAG), LLM Hallucination Detection, Generative AI pipelines and Responsible Generative AI. Demonstrated success in developing Time Series Analysis and Forecasting-based solutions. Adept in AWS as a Certified Cloud Practitioner, having developed end-to-end, cloud-based MLOps solutions centered around Machine Learning, Time Series Forecasting, and Generative AI. Simultaneously engaged in research work leading to the publication of research papers. Exhibiting exceptional problem-solving prowess and the capacity to articulate technical resolutions effectively to non-technical stakeholders. My accomplishments encompass delivering precise, data-driven insights that bolster business value. A proficient communicator who thrives in collaborative environments, driven by the desire to overcome complex challenges.Key Skillsets:- Programming Languages: Python and R- Data Science: NumPy, Pandas, Seaborn, Statsmodel, Time Series Analysis, and Forecasting, Machine Learning, Deep Learning, Scikit-Learn.- Tools and Software: AWS, Azure, Git & GitHub, VS Code, Jupyter Notebook, R Studio, and Weka.- Generative AI: RAG, LangChain, Vector Database(s), LLMs, Fine-Tuning LLMs, OCR, Responsible AI & GenAI, Prompt Engineering, Microsoft Azure Cognitive Services and OpenAI.