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Added 6 mins ago
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Director, Financial Planning & Analysis - SLC Management
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NRG

Data Scientist

Edmonton, AB, T5V 1J3, Canada
AB, Canada
Calgary, AB, T2P 3S8, Canada

Experience: 3+ years of experience in Data Science, advanced analytics, machine learning, forecasting, or related analytical roles.
Posting language: English
Posted: Sep 1, 2026

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Original job description

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 www.directenergy.com. Connect with NRG and Direct Energy on Facebook, LinkedIn, and follow us on Twitter.

JOB SUMMARY:

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.

KEY RESPONSIBILITIES

Data Science & AI Solutions

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.

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.

Business Partnership & Innovation

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.

Reporting & Decision Support

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.

Minimum Qualifications

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.

Preferred Qualifications:

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.

Additional Knowledge, Skills & Abilities

Ability to determine the most appropriate solution approach, whether reporting, analytics, machine learning, optimization, or AI.
Strong business acumen and problem-solving skills.
Excellent communication, data storytelling, and presentation skills.
Strong technical writing and documentation capabilities.
Ability to manage multiple priorities in a fast-paced environment.
Continuous learning mindset with interest in emerging AI and analytics technologies.

NRG Energy is committed to a drug and alcohol-free workplace. 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. Level, Title and/or Salary may be adjusted based on the applicant's experience or skills.

Official description on file with Talent.

We support the use of AI tools to help you prepare for your interview (e.g., practicing responses, researching the role, or refining your resume). However, during interviews and assessments, we expect responses to reflect your own thinking, experience, and communication. 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.

Apply About employer

More about this job

Responsibilities

The Data Scientist is responsible for developing, deploying, and monitoring advanced analytical, machine learning, and Generative AI solutions to improve customer outcomes and operational performance. They will partner with various business teams to transform data into actionable insights and manage the end-to-end lifecycle of analytical projects.

Requirements

Candidates must hold a bachelor's degree in a quantitative discipline and possess at least 3 years of experience in data science or advanced analytics. Proficiency in SQL and Python, along with experience in predictive modeling and data visualization, is required.

Skills

Data Science
Machine Learning
Generative AI
Python
SQL
Predictive Modeling
Forecasting
Optimization
Data Visualization
Power BI
Tableau
Statistical Analysis
Large Language Models
Model Validation
Data Pipelines

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Machine Learning
Generative AI
Python
SQL
Predictive Modeling
Forecasting
Optimization
Large Language Models
LLMs
RAG
Azure OpenAI
Databricks
MLflow
Azure AI
Power BI
Tableau
Data Visualization
Model Governance
Model Monitoring
Statistical Analysis
Customer Care Analytics
Workforce Management
Data Pipelines
Business Intelligence
Quantitative Analysis
Automation
Data Storytelling
Operations Research
Cloud Platforms

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