Data Scientist F/H - Informatique de gestion (H/F)

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 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.
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, LinkedIn, 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.

Data Science & AI Solutions
Develop and deploy statistical, machine learning, forecasting, optimization, and Generative AI solutions that improve customer outcomes and operational performance.
Evaluate when reporting, advanced analytics, machine learning, or LLM-based solutions are the most appropriate approach.

Model Development, Validation & Monitoring
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.

Data & Technical Delivery
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.
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.
• Strong proficiency with SQL and Python.
• 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), Retrieval-Augmented Generation (RAG), and AI assistants.
Experience with Azure OpenAI, Databricks, MLflow, Azure AI, or similar cloud-based AI platforms.
Strong understanding of statistics, machine learning, forecasting, and Generative AI technologies.
Experience with model validation, model governance, and model monitoring practices.
Experience with forecasting, optimization, contact center analytics, workforce management, collections, or customer care operations.
Experience deploying and supporting production machine learning solutions.
Knowledge of responsible AI, model explainability, and AI governance principles.

Ability to determine the most appropriate solution approach, whether reporting, analytics, machine learning, optimization, or AI.
Excellent communication, data storytelling, and presentation skills.
Strong technical writing and documentation capabilities.
Continuous learning mindset with interest in emerging AI and analytics technologies.

To the extent permitted by law and any applicable collective bargaining agreement, employees are subject to periodic random drug testing, and post-accident and reasonable suspicion drug and alcohol testing. EOE AA M/F/Vet/Disability. We support the use of AI tools to help you prepare for your interview (e.g., Use of AI to generate or read answers in real time, complete assessments, or misrepresent your qualifications is not permitted and may impact your candidacy.