Job Description - Data Scientist



Job Title: Data Scientist


Location: Wayne, IN 46809 (Hybrid)


Duration: 6-12 months contract


 


Position Summary:


·         We are seeking a highly skilled and motivated Data Scientist with a strong background in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.


·         The ideal candidate has direct experience applying AI within the utility, energy, or industrial sector.


·         You will lead the design, development, and deployment of intelligent systems that translate unstructured operational data (technical manuals, maintenance logs, field reports) into actionable insights.


Key Responsibilities:


·         Develop RAG Pipelines: Design and optimize Retrieval-Augmented Generation (RAG) models to enhance LLM-driven troubleshooting and field operations.


·         AI Model Development: Fine-tune and evaluate LLMs (e.g., GPT-4, Llama 3) for task-specific reasoning and accuracy.


·         Knowledge Integration: Build high-quality Python code to integrate vector databases (e.g., Pinecone, Milvus, Weaviate) to store and retrieve technical utility documents efficiently.


·         Operational Intelligence: Apply LLM solutions to analyze unstructured utility data, such as asset management logs, SCADA alerts, and maintenance records.


·         Deployment: Work with software engineers to deploy and scale models in cloud environments (Azure/AWS).


·         Collaboration: Work cross-functionally with field operations, engineering teams, and stakeholders to understand data needs and deliver solutions.


 


Required Qualifications:


·         Experience: Professional experience in Data Science/Machine Learning, with at least 1 year focusing specifically on LLMs and Generative AI.


·         Technical Skills: Advanced proficiency in Python (PyTorch/TensorFlow, LangChain, LlamaIndex) and SQL.


·         Domain Knowledge: Proven experience in the utility, energy, oil & gas, or heavy industrial sectors.


·         RAG Expertise: Hands-on experience with vector embeddings, semantic search, and prompt engineering.









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