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# Sr Data Scientist

- **Company:** NRG Energy, Inc
- **Location:** Houston, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Python (Programming Language), Machine Learning, Cloud Services, SQL Databases, Large Language Models, Multi-Agent Systems, Prompt Engineering, Apache Spark, Generative AI, Machine Learning Operations, Virtual Agents, Databricks
- **Published:** July 11, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/87604040/1

## About the Role

* Experience: 10+ years in Data Science or a related analytical role, with a proven track record of deploying production-grade AI.
 * Technical Stack: Advanced proficiency in Python, SQL, cloud data platforms, and MLOps frameworks.
 * AI Specialization: Hands-on experience with Large Language Models (LLMs), prompt engineering, vector databases, and conversational AI architecture.

## Description

We are seeking an innovative Senior Data Scientist to lead the design, deployment, and optimization of machine learning and Generative AI solutions for our customer care ecosystem. This role bridges Customer Care Operations, Product, IT, and Data Engineering to translate complex business needs into scalable AI products that improve customer experience and operational efficiency., * AI & Machine Learning Development: Design, train, and deploy predictive models (classification, forecasting, anomaly detection). Build and optimize Generative AI applications, Retrieval-Augmented Generation (RAG) systems, and multi-agent workflows.

 * Customer Care AI Solutions: Develop and evaluate AI tools supporting Agent Assist, Virtual Agents, intelligent routing, speech/sentiment analytics, and workflow automation.
 * Advanced Analytics & Experimentation: Analyze large-scale structured and unstructured datasets. Create forecasting models for contact volumes and customer churn, and establish A/B testing frameworks.
 * Data Engineering & MLOps Infrastructure: Partner with data teams using Databricks, Spark, SQL, and Python to build ETL pipelines, vector databases, and model serving infrastructure. Maintain CI/CD workflows and monitor for data/model drift in production.
 * Governance & Leadership: Ensure all AI solutions comply with data privacy and Responsible AI metrics. Mentor technical practitioners and present key findings to executive stakeholders.


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