Data Science Analyst - Agentic AI Developer

NRG•Houston, TX

2d•Onsite

About The Position

NRG Energy is seeking a Data Science Analyst – Agentic AI Developer to design, develop, and deploy AI-powered solutions that improve decision-making, automate business processes, and generate actionable insights across the organization. This role combines data science, machine learning, software engineering, and agentic AI development to solve complex business challenges in the energy industry. The ideal candidate is comfortable working across the full AI lifecycle—from data acquisition and model development to deployment, monitoring, and continuous improvement—and thrives in a collaborative, fast-paced environment.

Requirements

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Quantitative Finance, or a related quantitative discipline; Master's degree preferred.
Three or more years of professional experience in data science, machine learning, AI application development, or advanced analytics.
Strong proficiency in Python and SQL, with experience processing large datasets and developing production-quality software.
Experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar technologies.
Experience developing AI applications using LLMs, prompt engineering, RAG, AI agent frameworks, vector databases, REST APIs, and modern software development tools (Git, Docker).
Experience with cloud platforms (AWS, Azure, or Google Cloud), data visualization tools (Power BI, Tableau, Plotly, or Matplotlib), and building scalable data pipelines.
Strong understanding of statistics, feature engineering, model evaluation, and MLOps fundamentals.
Excellent analytical, communication, and problem-solving skills, with the ability to independently manage multiple priorities, collaborate across multidisciplinary teams, and deliver high-quality AI solutions with professionalism, integrity, and a commitment to continuous learning.

Nice To Haves

Experience with LangGraph, LangChain, Semantic Kernel, CrewAI, or similar orchestration frameworks; NLP, Generative AI, Computer Vision, Spark, Databricks, MLflow, Kubernetes, time-series forecasting, energy markets, or cloud-native AI services (e.g., Azure OpenAI, Amazon Bedrock, Google Vertex AI) is highly desirable

Responsibilities

Collect, clean, integrate, and preprocess large structured and unstructured datasets to support advanced analytics, machine learning, and AI applications.
Design, develop, deploy, and optimize machine learning models for forecasting, predictive analytics, anomaly detection, recommendation systems, classification, and operational optimization.
Build AI-powered applications using large language models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, APIs, and workflow automation to improve productivity and streamline business processes.
Rapidly prototype, test, and deploy scalable AI solutions, translating ambiguous business challenges into practical, production-ready applications.
Develop scalable data pipelines, reusable software components, APIs, and AI workflows that integrate enterprise data sources and operational systems.
Collaborate with business stakeholders, software engineers, data engineers, analysts, and subject matter experts to integrate AI capabilities into business workflows.
Analyze complex datasets to identify trends, generate actionable insights, and communicate findings through dashboards, reports, and data visualizations for both technical and non-technical audiences.
Monitor, evaluate, and continuously improve AI models and applications to ensure accuracy, scalability, reliability, governance, and responsible AI practices.
Stay current with emerging AI, machine learning, and data science technologies, evaluating opportunities to drive innovation and business value.