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 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) .