Lead Data Scientist (Agentic AI & RAG)

Job description

**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 Learning - Data Science and end-to-end ML solution development - Statistical Analysis (probability, hypothesis testing, regression analysis, Bayesian statistics, A/B testing) - NLP and LLM development for semantic understanding and language tasks - Agentic AI and RAG (retrieval-augmented generation) for enterprise LLM applications Good to Have: - Deep Learning and Generative AI experience - Semantic AI experience **Education:** Master's or PhD in Computer Science, Statistics, Mathematics, or a related field (or equivalent practical experience)