Lead Data Scientist (Agentic AI & RAG)

Key Skills: Agentic AI, LLM, AI/ML, Data Scientist, Statistical Analysis, NLP, Retrieval-Augmented Generation (RAG), Semantic AI, Generative AI, Deep Learning Roles and Responsibilities: Design and develop AI agents and multi-agent systems using LangGraph, LangChain, and Semantic Kernel.Build and productionize LLM applications using RAG architectures, including retrieval pipelines and ranking strategies.Develop machine learning models for classification, regression, forecasting, recommendations, and anomaly detection.Implement NLP solutions such as text classification, entity extraction, semantic search, conversational AI, and sentiment analysis.Apply statistical modeling and experimental design to validate model performance and drive data-driven decisions.Skills Required: 6-7 years of experience in Data Science and Machine LearningData Science and end-to-end ML solution developmentStatistical Analysis (probability, hypothesis testing, regression analysis, Bayesian statistics, A/B testing)NLP and LLM development for semantic understanding and language tasksAgentic AI and RAG (retrieval-augmented generation) for enterprise LLM applicationsGood to Have: Deep Learning and Generative AI experienceSemantic AI experienceEducation: Master's or PhD in Computer Science, Statistics, Mathematics, or a related field (or equivalent practical experience) .