Developed an end-to-end NLP-based financial advisory system that delivers personalized investment insights from real-time news. Built a complete data pipeline including news scraping, preprocessing, NER, sentiment analysis, and financial entity mapping. Implemented semantic search using embeddings and vector database, and applied Retrieval-Augmented Generation (RAG) with LLMs to generate tailored recommendations based on user profiles.

Worked on analyzing real-world datasets to extract meaningful insights and support data-driven decisions. Built interactive dashboards to visualize key metrics and trends. Performed data querying and analysis using MySQL to generate actionable business insights. Cleaned, processed, and analyzed multiple CSV datasets using Python libraries such as NumPy and Pandas. Created insightful visualizations using Matplotlib and Seaborn. Additionally, trained and evaluated machine learning models to identify patterns and improve predictive understanding.