Design, build, and maintain forecasting and optimization models embedded in core product workflows
Model asset behavior, weather impacts, and behind-the-meter resources
Translate operational and business requirements into quantitative frameworks and production systems
Own the full lifecycle of quantitative systems — from data ingestion, pipelines, schemas, and interfaces through deployment, monitoring, and reliability in production
Establish best practices for model development, validation, performance monitoring, and operational robustness
Partner closely with engineering to define interfaces, data contracts, and system boundaries that enable robust quantitative services
Provide technical leadership and guidance on quantitative methods across the organization

7+ years of experience in data science, applied statistics, quantitative engineering, or related fields
Real-world experience building electric load forecasting models
Strong understanding of constraint programming and multi-objective optimization for real-time systems
Experience building optimization models and implementing them in energy / capacity markets
Background in time-series analysis and regression-based modeling
Proven experience deploying and maintaining models in production environments
Comfort working with highly variable real-world data from numerous and varying sources, and building the supporting infrastructure
Strong programming skills in Python (or similar)
Ability to operate autonomously and make sound technical trade-offs
Strong communication skills across technical and non-technical audiences

Data Scientist

Key skills