Lead AI Analytics Scientist — RAG & LLM Expert

National Grid; City of Syracuse (NY); Hybrid; USD 136,000 - 192,000; Full time

Job summary

National Grid is seeking a Lead Data Scientist to lead AI-enabled analytics for the Customer Performance Lab. This hybrid role spans Syracuse, Brooklyn, Hicksville, NY and Waltham, MA, with work-from-home options.

You will design RAG-based analytics, build knowledge stores, and drive AI adoption across Customer Operations. The candidate will collaborate with IT and Transformation teams, develop scalable AI solutions, and influence decision-making through data-driven insights.

Qualifications

• Bachelor's/Master's/PhD in a quantitative field.
• Strong Python development and production analytics experience.
• Experience with enterprise AI technologies and LLM APIs.
• Experience with Retrieval-Augmented Generation and vector search.

Responsibilities

• Design, develop and optimize RAG solutions with enterprise knowledge stores.
• Build AI knowledge architectures and semantic models.
• Develop reusable AI skills, agents, copilots and prompts.
• Lead AI cost optimization while maintaining performance.
• Partner with engineering to deploy AI in business applications and dashboards.
• Hands-on experience building RAG solutions.
• Work with vector databases, embeddings, and semantic search.
• Integrate LLMs via APIs (OpenAI, Snowflake Cortex, Databricks AI).
• Apply prompt engineering and evaluation frameworks.

Skills

Python

Data science

AI/LLMs

SQL

Cloud platforms

APIs

RAG

Education

Bachelor's/Master's/PhD in Data Science or related

Tools

Snowflake

Databricks

OpenAI API

Cortex

Job description

National Grid is seeking a Lead Data Scientist to lead AI-enabled analytics for the Customer Performance Lab. This hybrid role spans Syracuse, Brooklyn, Hicksville, NY and Waltham, MA, with work-from-home options.

You will design RAG-based analytics, build knowledge stores, and drive AI adoption across Customer Operations. The candidate will collaborate with IT and Transformation teams, develop scalable AI solutions, and influence decision-making through data-driven insights.