1 день назад
Senior Data Scientist (Energy)
190 000 - 230 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Scientist (Energy) (Machine Learning/Forecasting): Building and deploying production-grade forecasting models for distributed battery storage, demand response, renewable energy, and electricity market participation with an accent on time series forecasting, uncertainty quantification, and energy systems modeling. Focus on leading advanced research, designing machine learning workflows for battery optimization, and solving complex decision-making problems under uncertainty.
Location: San Francisco, CA (Hybrid)
Base salary: $190,000–$230,000 per year
Company
builds an energy intelligence platform that helps large energy consumers manage power portfolios and operate distributed energy assets for the AI economy.
What you will do
- Design, develop, and deploy production-grade machine learning models for energy forecasting.
- Build forecasting workflows supporting optimization and control of battery storage, demand response, and electricity market participation.
- Apply statistical analysis, simulations, and energy modeling to renewable resources, storage systems, and emerging technologies.
- Lead and contribute to research on solar, wind, energy storage, green hydrogen, and other energy systems.
- Collaborate with data scientists, software engineers, business units, and customers to apply research to real-world problems.
Requirements
- At least 5 years of experience deploying machine learning forecasting algorithms in production software environments.
- At least 2 years of experience applying forecasting methods in the energy industry.
- Experience with machine learning, deep learning, time series forecasting, and uncertainty quantification.
- Strong expertise in statistical methods, forecasting, and energy systems.
- Highly proficient in Python and data analysis tools.
- Knowledge of electricity markets and energy technologies including solar, wind, battery storage, and grid integration.
Nice to have
- PhD in Engineering, Operations Research, Economics, or a related field.
- Knowledge of mathematical and stochastic optimization.
- Experience deploying machine learning or deep learning models for battery operation forecasting.
- Experience with power markets forecasting.
Culture & Benefits
- Empathetic, humble, and collaborative working environment.
- Emphasis on honesty, transparency, and effective communication.
- Flexible hours and unlimited paid time off.
- Medical, dental, and vision insurance, plus a 401(k).
- Equity grant and an inclusive workplace focused on sustainability.
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