Drive profitability and retention for NRG Consumer by applying machine learning foundations and practical business modeling experience.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
Data Scientist – Price Optimization & Churn Forecasting
Fully Remote
Compensation: $65/Hour W2
Oil/Energy
Overview
This role focuses on price optimization, churn forecasting, and customer analytics to drive profitability and retention for NRG Consumer. The ideal candidate brings strong machine learning foundations, practical business modeling experience, and the ability to translate analytics into measurable business impact.
The most recent hire in this space was a Data Scientist with a PhD in Economics and strong causal inference experience, which reflects the caliber and analytical rigor desired for this role.
Project Overview
Project Focus
Price optimization
Customer churn forecasting
Profit and margin improvement
Customer behavior and retention modeling
Project Type
Implementation and enhancement
Production analytics and modeling
Tech Stack
Python
PySpark
Databricks
Cloud-based data platforms
Machine learning and statistical modeling libraries
Job Summary
Welcome to NRG and the epicenter of personal power. We’re driven by the idea of a smarter, cleaner, digitally-enhanced energy ecosystem—and the possibilities that brings to the world and to the seven million customers we serve.
NRG Consumer data scientists blend technical expertise and business acumen to help NRG brands achieve financial and strategic objectives. This role is hands-on and learning-oriented, emphasizing real-world analytics and modeling.
Key Responsibilities
Adhere to NRG’s culture of humility, curiosity, and impact
Process and analyze large datasets using Python, PySpark, and Databricks
Develop predictive models and analytical dashboards
Apply machine learning to real business problems such as churn, pricing, and forecasting
Partner with business stakeholders to enable data-driven, profitable decisions
Translate customer and prospect insights into actionable recommendations
Must-Have Qualifications (Non-Negotiables)
Machine Learning and Analytics
Proven experience applying machine learning to real-world business problems
Ability to clearly explain what business problems machine learning is solving, such as churn, pricing, forecasting, or personalization
Retail or Consumer Analytics Experience
Experience in one or more of the following areas:
Customer churn and retention
Pricing strategies and optimization
Profit and margin improvement
Subscription-based business models
Customer loyalty and engagement
Sales growth initiatives
Business Impact Focus
Demonstrated ability to use data science to improve customer experience and business profitability
Technical Skills
Strong Python proficiency with hands-on experience in PySpark, NumPy, pandas, scikit-learn, XGBoost, Matplotlib, and lifelines
Communication and Collaboration
Strong cross-functional communication skills
Ability to work effectively with product, marketing, analytics, and business teams
Comfortable communicating insights to both technical and non-technical audiences
Preferred or Negotiable Qualifications
PhD in a quantitative discipline such as Economics, Statistics, or Mathematics
Deep knowledge of causal inference, forecasting, optimization, frequentist and Bayesian statistics, machine learning, and natural language processing
Experience with version control
Experience reading and writing cloud-based data
Experience and Education
Minimum Requirements
0 to 3 years of experience in data analysis or a related field
Master’s degree in a quantitative discipline or equivalent practical experience
Experience with statistical software and database languages