Note: The job is a remote job and is open to candidates in USA. Electrify America is committed to revolutionizing the way people charge and is seeking a Senior Data Scientist, Energy to develop the analytical foundation for managing energy costs across its open DC fast charging network. This role will leverage expertise in utility tariffs, wholesale energy markets, and predictive modeling to drive cost optimization and support real-time operational decision-making.
Responsibilities
- Develop and maintain the analytical framework used to model energy costs across Electrify America's network of 1,000+ charging sites spanning more than 250 utility territories
- Research, interpret, and maintain utility tariff data, translating complex rate structures into scalable analytical models and operational systems
- Build and enhance models that quantify energy costs at a granular session level, including demand charges, energy charges, and other tariff-based cost drivers
- Develop methodologies and models that incorporate wholesale energy market dynamics, including hourly pricing, critical event pricing, and nodal market signals
- Design predictive models that estimate marginal utility costs and collaborate with energy services and engineering teams to deploy these insights into real-time operational applications
- Partner with pricing, energy services, and network P&L management teams to develop recurring reporting and ad hoc analyses on network economics and profitability
- Quantify and track financial savings generated through tariff optimization, energy market participation, and other cost management initiatives across Electrify America, Electrify Canada, and commercial charging customers
- Translate analytical findings into clear recommendations for business, operational, and strategic decision-making
- Collaborate across functions to improve data quality, analytical capabilities, and operational performance
Skills
- 7+ years of experience in data science, quantitative analytics, energy economics, utility analytics, or related fields
- Bachelor's degree in Economics, Mathematics, Engineering, Computer Science, Statistics, or a related quantitative discipline
- Deep knowledge of commercial and industrial utility rate structures, including demand charges, time-of-use rates, and rate optimization
- Experience analyzing wholesale electricity markets and hourly energy price signals
- Strong quantitative and analytical skills with demonstrated ability to transform complex datasets into actionable insights
- Advanced proficiency in Python, SQL, and Excel
- Experience building scalable and repeatable analytical models and workflows
- Strong understanding of statistical analysis, forecasting, and econometric techniques
- Ability to work effectively with incomplete, imperfect, and evolving datasets
- Proven ability to independently lead projects and drive execution in ambiguous environments
- Exceptional written, verbal, and presentation communication skills
- Demonstrated attention to detail, accountability, and integrity
- Experience applying machine learning techniques to forecasting or optimization problems, including time-series forecasting methods (e.g., ARIMA, LSTM, or related approaches)
- Experience deploying analytical models into production environments using AWS or other cloud platforms
- Familiarity with EV charging, transportation electrification, energy infrastructure, utility operations, or broader energy transition sectors
- Advanced degree in Economics, Mathematics, Engineering, Computer Science, Statistics, or a related quantitative field
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