Sr. Data Scientist/ Lead Data Scientist

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Techmatic Inc, is seeking the following. Apply via Dice today! Contract role - Sr. Data Scientist to Lead level Required Experience Hands-on experience with LLMs, including prompt engineering, fine-tuning, or agentic architectures (LangGraph, AutoGen, CrewAI, etc.). Strong programming skills in Python, with experience in building scalable ML/AI applications. Model evaluation expertise for LLM-based systems, including designing metrics and running A/B tests or offline experiments. Python LangChain / LangGraph / CrewAI / AutoGen (any relevant) Hugging Face Transformers Vector DBs (e.g., FAISS, Weaviate, Pinecone) Git, VS Code, and cloud platforms (Google Cloud Platform preferred) Contribute to the development of a Knowledge Assistant for the Pro & Services organization, with a focus on natural language understanding and agentic workflows. Build, evaluate, and iterate on LLM-powered agents to support task execution, reasoning, and retrieval across structured and unstructured data. Collaborate closely with product managers, engineers, and other data scientists to integrate intelligent systems into customer and associate-facing platforms. Own model evaluation and validation pipelines, especially for LLM and RAG workflows, including performance tracking and ablation studies. Write clean, production-grade Python code and contribute to reusable components and pipelines. Apply critical thinking and analytical problem-solving to identify patterns, define rules, and optimize agent behaviors. Preferred Experience Experience with retrieval-augmented generation (RAG) and knowledge graphs, vector Databases. Retail or digital experience Designing custom evaluation pipelines for hallucination detection, factual consistency, and user relevance. Familiarity with frameworks like TruLens, Ragas, Promptfoo, or ReAct-style evaluation loops. Implementing guardrails to ensure safety, compliance, or brand alignment in LLM outputs. Prior exposure to PhD-level research or applied LLM work in industry or academia. Disqualifiers Generic ML experience without any LLM, agentic, or applied AI work. Heavy reliance on low-code/no-code ML platforms without demonstrated software engineering capability. Lack of hands-on involvement in end-to-end model deployment or evaluation. Team environment The candidate will join a tight-knit, cross-functional AI team focused on building LLM-powered capabilities for Pro and Services use cases. The team includes Data Scientists, AI Engineers and a AI Product Manager The environment is collaborative and fast-paced, with strong product orientation, a culture of rapid experimentation, and close alignment with business stakeholders. Candidates should be comfortable with ambiguity, quick pivots, and high-impact deliverables. Any Additional Details: Ideal for someone passionate about pushing the boundaries of LLM applications in real-world settings. There's significant opportunity to shape foundational tools that will power experiences for Pro customers and store associates.