Staff Data Scientist, AI - Hybrid
Role details
Job location
Tech stack
Job description
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
Requirements
- Proven expertise in predictive modeling, forecasting, and applied ML (e.g., regression, gradient boosting, time-series, causal
inference).
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Experience working with large-scale event and sensor data, preferably within energy, IoT, or device-driven ecosystems.
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Strong proficiency in Python (Pandas, NumPy, scikit-learn, PySpark) and experience with distributed compute environments
(Spark, Databricks, GCP).
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Ability to take models from concept to production in collaboration with engineering partners.
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Skilled in statistical analysis, feature engineering, and experimental design (e.g., A/B testing).
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Excellent communication and storytelling skills for complex, data-driven topics.
Preferred Qualifications
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Experience with energy forecasting, thermal modeling, or Demand Response optimization.
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Understanding energy markets, Distributed Energy Resources (DER), and Virtual Power Plant (VPP) concepts.
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Familiarity with LLM or generative AI applications in analytics and optimization.
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Advanced degree in a quantitative field such as Statistics, Computer Science, or Engineering.
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5+ years of industry experience, including demonstrated technical leadership on high-impact modeling initiatives.