Staff Data Scientist, AI - Hybrid

NRG Energy

Lehi, Utah, United States

Lehi, Utah, United States

Über

Welcome to the intersection of energy and home services. At NRG, we're driven by our passion to create a smarter, cleaner and more connected future. Vivint Smart Home, an NRG owned company, is a leading smart home company in the United States, dedicated to redefining the home experience with intelligent products and services. We find purpose in proactively protecting and keeping our customers connected to home, no matter where they are. Join the Smart Home team to create smarter, safer and more sustainable homes. About This Role Vivint, an NRG Company, is redefining home energy intelligence through data and AI to enable personalized comfort, energy efficiency, and demand-response optimization across millions of connected homes. We are seeking a Staff Data Scientist to design and deploy predictive models that enable intelligent home energy decisions: from forecasting comfort and cost to optimizing EV charging and demand response events. * Develop Predictive Models: Build and deploy advanced models for occupancy, runtime, cost forecasting, anomaly detection, and preconditioning to enable comfort-aware, energy-efficient control and maintenance. * Optimize Energy Operations: Use data-driven insights to improve the reliability and precision of Demand Response (DR), Time-of-Use (TOU) shifting, and Virtual Power Plant (VPP) strategies. * Advance Data Quality & Scalability: Partner with data engineering to transform legacy data structures into robust, documented, and reusable data products that support ML and real-time analytics. * Cross-Functional Collaboration: Work closely with product, engineering, and analytics teams to embed intelligence into production systems and shape future data-driven energy experiences. * Communicate Impact: Translate complex model outcomes into actionable insights for both technical and non-technical audiences.
Required Qualifications * Proven expertise in predictive modeling, forecasting, and applied ML (e.g., regression, gradient boosting, time-series, causal inference). * Experience working with large-scale event and sensor data, preferably within energy, IoT, or device-driven ecosystems. * Strong proficiency in Python (Pandas, NumPy, scikit-learn, PySpark) and experience with distributed compute environments (Spark, Databricks, GCP). * Ability to take models from concept to production in collaboration with engineering partners. * Skilled in statistical analysis, feature engineering, and experimental design (e.g., A/B testing). * Excellent communication and storytelling skills for complex, data-driven topics.
Preferred Qualifications * Experience with energy forecasting, thermal modeling, or Demand Response optimization. * Understanding energy markets, Distributed Energy Resources (DER), and Virtual Power Plant (VPP) concepts. * Familiarity with LLM or generative AI applications in analytics and optimization. * Advanced degree in a quantitative field such as Statistics, Computer Science, or Engineering. * 5+ years of industry experience, including demonstrated technical leadership on high-impact modeling initiatives.
This is a hybrid role that requires 4 days in the office. (Mon-Thurs)
If you reside in or intend to work remotely from California, Colorado, Connecticut, Hawaii, Illinois, Minnesota, Nevada, New York, Ohio, Washington D.C., Washington State or another state or locality with a pay transparency law, you may contact
for compensation information related to this position and other information as required by applicable law. Please include the job title in your request.
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.

Lehi, Utah, United States

Sprachkenntnisse

English

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