PhD Level - Data Scientist

Job Summary Core Responsibilities • Develop and enhance a Knowledge Assistant for the Pro & Services organization focused on natural language understanding and agentic workflows. • Build, evaluate, and iterate on LLM-powered agents for task execution, reasoning, and data retrieval (structured and unstructured). • Collaborate with product managers, engineers, and other data scientists to integrate AI solutions into customer and associate-facing platforms. • Design and own model evaluation and validation pipelines for LLM and RAG workflows, including performance tracking and ablation studies. • Write clean, production-grade Python code and reusable ML/AI components. • Apply analytical problem-solving to identify patterns, define rules, and optimize agent behavior. Required Qualifications • PhD-level research or applied experience with LLMs and AI. • Deep expertise in LLMs, including prompt engineering, fine-tuning, or agentic architectures (e.g., LangGraph, AutoGen, CrewAI). • Strong software engineering background; extensive hands-on Python programming skills. • Experience with LangChain and/or LangGraph. • Hands-on model evaluation expertise for LLM-based systems, including metric design and A/B or offline testing. Additional/Preferred Skills • Experience with agentic or applied AI projects. • Familiarity with tools like CrewAI, AutoGen, Hugging Face Transformers, vector DBs (FAISS, Weaviate, Pinecone). • Proficiency with Git, VS Code, and cloud platforms (GCP preferred). • Experience with retrieval-augmented generation (RAG), knowledge graphs, and custom evaluation pipelines. • Retail or digital domain experience. • Familiarity with evaluation frameworks (TruLens, Ragas, Promptfoo, ReAct-style). • Experience implementing guardrails for LLM safety, compliance, and brand alignment. Disqualifiers • Only generic ML experience without LLM or advanced AI work. • Heavy use of low-code/no-code ML platforms without software engineering depth. • Lack of end-to-end hands-on involvement in model deployment or evaluation. Key Traits • Self-starter, curious, able to navigate ambiguity, and thrive in a fast-moving, high-impact AI innovation team. • Strong communication skills to articulate technical LLM/AI experience. Let me know if you need a shorter summary or a version tailored for a resume or job posting!