Agentic AI Developer & Data Scientist

NRG Energy, Inc.; Houston (TX); On-site; USD 60,000 - 80,000; Full time

Job summary

NRG Energy, Inc. is seeking a Data Science Analyst – Agentic AI Developer to design, develop, and deploy AI-powered solutions that improve decision-making, automate processes, and generate actionable insights across the organization.

You’ll work across the AI lifecycle from data collection and model development to deployment, monitoring, and continuous improvement in a fast-paced energy environment. The role requires collaboration with data engineers, software developers, and business

Qualifications

• Bachelor’s degree in a quantitative field by Dec 2026; Master’s preferred.
• Experience in data science, ML, AI or advanced analytics is a plus.

Responsibilities

• Collect, clean, integrate, and preprocess large datasets for analytics and AI.
• Design, develop, deploy, and optimize ML models for forecasting and analytics.
• Build AI-powered apps using LLMs, RAG, AI agents, APIs, and workflow automation.
• Prototype, test, and deploy scalable AI solutions for business problems.
• Develop scalable data pipelines, APIs, and AI workflows integrating enterprise data.
• Collaborate with engineers, analysts, and stakeholders to embed AI into workflows.
• Analyze data to identify trends and communicate findings via dashboards and visualizations.
• Monitor and improve AI models for accuracy, scalability, and governance.
• Stay updated on AI trends to drive innovation and value.

Skills

Python

SQL

ML frameworks

LLMs

RAG

REST APIs

Git/Docker

Education

Bachelor's degree in Data Science/CS/Statistics/Engineering

Master’s degree preferred

Tools

Docker

Kubernetes

Spark/Databricks

MLflow

Python data libraries

Job description

NRG Energy, Inc. is seeking a Data Science Analyst – Agentic AI Developer to design, develop, and deploy AI-powered solutions that improve decision-making, automate processes, and generate actionable insights across the organization.

You’ll work across the AI lifecycle from data collection and model development to deployment, monitoring, and continuous improvement in a fast-paced energy environment. The role requires collaboration with data engineers, software developers, and business