Senior Data Science Lead - R01551335

Key Responsibilities

• Design and develop advanced statistical and machine learning models including regression, classification, forecasting, and hypothesis testing techniques
• Build and optimize Agentic AI systems using frameworks such as LangGraph for multi-agent orchestration and autonomous decision-making
• Develop memory-augmented, context-aware AI agents capable of reasoning, planning, and executing tasks across enterprise domains
• Implement LLM orchestration pipelines integrating RAG (Retrieval-Augmented Generation), vector databases (FAISS, Pinecone, Weaviate), and knowledge graphs
• Apply reinforcement learning techniques (RLHF/RLAIF) to improve AI agent performance and decision-making capabilities
• Architect scalable AI solutions integrating LLMs with enterprise systems and workflows
• Lead research and experimentation in Agentic AI, multi-agent systems, and self-improving AI frameworks
• Develop and deploy ML models using Python, PySpark, TensorFlow, PyTorch, Scikit-learn, Keras, and other frameworks
• Build and maintain end-to-end ML pipelines using tools such as Kubeflow and BentoML
• Ensure data quality, model monitoring, and validation using tools such as Great Expectations and Evidently AI
• Translate AI research into scalable enterprise solutions with measurable business impact
• Lead proof-of-concept (PoC) initiatives and scale successful models into production environments
• Mentor and guide AI engineers and data scientists in advanced AI methodologies and best practices