Senior Forecasting and Optimization Engineer

Role overview Develop forecasting and optimization capabilities that help distributed energy resources deliver reliable services to the electricity grid. This senior role combines applied data science, control methods, and production software, with work spanning model development, operational monitoring, and insight delivery to energy sector stakeholders.

Responsibilities - Build and improve robust energy forecasting models and control or optimization algorithms. - Design, test, and deploy production code for critical forecasting and optimization products. - Create tools to monitor model performance and assess operational quality. - Analyze large, complex energy datasets and turn findings into actionable insights. - Advise other engineers and scientists on machine learning, forecasting, and optimization methods. - Communicate results to varied audiences and coordinate across technical, product, and customer-facing teams.

Requirements - At least five years of experience in areas such as machine learning, statistical analysis, control systems, data visualization, or mathematical optimization. - At least three years of practical Python experience with scientific or machine learning libraries such as Pandas, NumPy, SciPy, scikit-learn, PyTorch, or TensorFlow. - Experience building data pipelines with large relational databases. - Strong mathematical reasoning and the ability to apply new methods to practical problems. - Skill in finding useful patterns in complex data and explaining analysis clearly to different audiences.

Nice to have - Experience completing a substantial research project, such as a graduate thesis. - Commercial experience with large time-series forecasting, large-scale optimization, or cloud-based machine learning products. - Strong grounding in mathematics and statistics, or experience using language models to accelerate software development.