Data Scientist

Welcome to the intersection of energy and home services. At Direct Energy, an NRG company, we're all about propelling the next generation of leaders forward. We are driven by our passion to create a smarter, cleaner and more connected future. We deliver innovative solutions that make our customers' lives easier - helping them power, protect, and intelligently manage their homes and businesses.

To do this, we need creative and talented people to join our company.

We offer a dynamic work environment and a unified and inclusive culture. Our company programs are designed to help employees develop the skills they need for success now and in the future. In everything we do, we aim to champion our employees and bring value to our customers, investors and society.

More information is available at  Connect with NRG and Direct Energy on Facebook, Linked In, and follow us on Twitter.

The Data Scientist, Customer Care Analytics is responsible for developing, validating, deploying, and monitoring advanced analytical, machine learning, and Generative AI solutions that improve customer outcomes, operational performance, employee productivity, and business decision-making.

This role partners closely with Customer Care, Collections, Billing, Workforce Management, Technology, and Business Leadership teams to transform data into actionable insights and scalable solutions. The successful candidate will identify opportunities to leverage reporting, advanced analytics, predictive modeling, optimization, Large Language Models (LLMs), and other AI technologies to address complex business challenges.

The role is accountable for the end-to-end lifecycle of analytical and AI solutions, including business problem definition, data acquisition, model development, validation, deployment, monitoring, governance, and business adoption. In addition to advanced analytical work, the role will contribute to reporting, dashboarding, and decision-support solutions that enable data-driven decision-making across Customer Care operations. The role aligns well with the capabilities of advanced analytics, machine learning, model monitoring, validation, and decision-support solutions described within existing enterprise analytics practices.

The role aligns well with the capabilities of advanced analytics, machine learning, model monitoring, validation, and decision-support solutions described within existing enterprise analytics practices.

• Develop and deploy statistical, machine learning, forecasting, optimization, and Generative AI solutions that improve customer outcomes and operational performance.
• Translate business problems into analytical approaches and actionable recommendations.
• Evaluate when reporting, advanced analytics, machine learning, or LLM-based solutions are the most appropriate approach.

• Design, build, validate, and maintain predictive, forecasting, and AI models.
• Establish model performance standards, monitoring frameworks, and governance controls.
• Identify model drift, performance degradation, and opportunities for retraining or enhancement.

• Acquire, integrate, and prepare data from multiple sources for analytical and AI applications.
• Develop scalable analytical workflows, data pipelines, and reusable data assets using modern analytics tools and platforms.
• Apply best practices for testing, documentation, version control, and deployment.

• Partner with business leaders and stakeholders to identify opportunities for analytics and AI to create business value.
• Communicate analytical findings and recommendations to technical and non-technical audiences.
• Evaluate emerging technologies and drive innovation through advanced analytics, AI, and automation initiatives.

• Develop dashboards, reports, scorecards, and data visualizations that support operational and strategic decision‑making.
• Translate analytical outputs into clear business insights and performance measures.
• Ensure reporting accuracy, consistency, and alignment with business definitions.

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or related quantitative discipline.
• 3+ years of experience in Data Science, advanced analytics, machine learning, forecasting, or related analytical roles.
• Experience developing predictive, forecasting, optimization, or statistical models in a business environment.
• Strong proficiency with SQL and Python.
• Experience working with large and complex datasets.
• Experience applying statistical analysis and quantitative problem‑solving techniques.
• Experience communicating analytical findings to non‑technical stakeholders.
• Experience developing dashboards or reports using Power BI, Tableau, or similar tools.

• Experience with Generative AI, Large Language Models (LLMs),…