Senior Data Scientist

Senior Data Scientist – GenAI / RAGLocation: Houston, TX – Onsite 3 Days/WeekType: Full-TimeInterview Process- 3 Internal Technical Rounds- 1 Mandatory Face-to-Face at Vendor Office – Santa Clara, CA- 1 Client DiscussionRole OverviewSeeking a Senior Data Scientist with a strong Traditional Data Science/ML background and hands-on GenAI, LLM, RAG, and Agentic AI experience. Candidates must have practical production implementation experience and strong client-facing communication skills.Key Responsibilities- Design, develop, and deploy ML, GenAI, RAG, and Agentic AI solutions.- Build enterprise RAG systems, AI chat interfaces, and knowledge solutions.- Translate business requirements into scalable ML/AI solutions.- Collaborate with client data science, engineering, product, and business teams.- Explain architecture decisions, technical trade-offs, and solutions to stakeholders.Required Skills- Strong Data Science & Machine Learning experience.- Hands-on LLM, RAG, Agentic AI & Multi-Agent Systems.- LangChain, LangGraph, MCP, Tool Calling, Agent Orchestration.- RAG: Vector Databases, Hybrid Retrieval, Reranking, Knowledge Graphs.- Strong Python & SQL.- ML: Classification, Regression, Forecasting, Anomaly Detection, Feature Engineering, Model Evaluation.- XGBoost, CatBoost, Random Forest, PyTorch/TensorFlow.- Production AI/ML deployment and MLOps/LLMOps.- LLM evaluation, hallucination detection, groundedness, and retrieval-quality metrics.- AWS Bedrock; exposure to Azure OpenAI or Vertex AI is a plus.- Strong client-facing and stakeholder communication skills.Data & Cloud EnvironmentAWS, AWS Bedrock, Snowflake, Databricks, Spark, Vector Databases, APIsPreferred- Master's/Ph.D. in Computer Science, Statistics, Mathematics, or related field.- Enterprise product, consulting, or customer-facing experience.Important: We are specifically looking for candidates who have evolved from traditional Data Science/ML into GenAI/Agentic AI. Candidates with only recent or exploratory GenAI/LLM experience will not be a fit.