Data Scientist

• Train and evaluate forecasting models for new applications and use cases.
• Develop features for nodal electricity price forecasts, working with power market experts to identify predictive signals and integrate them into forecasting infrastructure.
• Investigate model behavior in specific contexts, such as diagnosing forecast misses and identifying root causes.
• Benchmark model performance by analyzing price forecast and battery dispatch backtests, defining metrics, and building dashboards to track them over time.

This role directly contributes to the clean energy transition by improving the accuracy of price forecasts and optimization algorithms for renewable energy storage, enabling more profitable and efficient operation of renewable energy infrastructure.

• Master’s degree in CS/Statistics/Finance/Operations Research OR 2 years of experience in related fields.
• Experience with Python and its package ecosystem (Pandas, PyTorch, plotting libraries), as well as SQL.
• Experience with time series forecasting, ideally at high frequency and demonstrated by concrete projects.
• Comfortable with machine learning models and concepts, and working in Git.

Salary: $130K - $170K. Benefits include parental leave, medical benefits, unlimited PTO, equity options, and a flexible work environment with hybrid/remote options and team offsites.

Tyba is a modeling platform for energy companies developing, financing, and operating renewable energy infrastructure. Their mission is to make cutting-edge models accessible to cross-functional teams to build and operate more renewable energy more profitably.