Mohib K is a highly skilled Data Scientist with strong foundations in computer science and hands-on experience building production-grade AI and data systems. He specializes in large language model (LLM) applications, Retrieval-Augmented Generation (RAG), and intelligent data access systems, with proven expertise using LlamaIndex, FastAPI, Python asyncio, AWS Bedrock, OpenSearch, and modern embedding models. At Xavor Corporation, he has architected and optimized enterprise RAG and Text-to-SQL systems serving dozens of concurrent users, enabling non-technical stakeholders to query complex databases and generate insights, visualizations, and reports with high accuracy and scalability. His work spans LLM evaluation, vector database design, schema-aware NLP pipelines, semantic search, document processing across diverse file formats, and adaptive chunking strategies to maximize retrieval relevance. Previously, as a Software Engineer at Techlogix, he developed feature-driven credit scoring and explainable machine learning scorecards using statistical modeling, PCA, WOE binning, and logistic regression. Backed by a BSc in Computer Science and experience in teaching, Mohib combines strong theoretical knowledge with practical system design, data analytics, and machine learning expertise to deliver robust, scalable, and business-impacting AI solutions.