ISO New England is seeking to enhance its forecast blending process to improve forecast accuracy and ensure reliable power system operations in the New England region.
Requirements
- Strong foundation in statistics, time series analysis, and machine learning.
- Experience with Python (NumPy, Pandas, ect) or R.
- Familiarity with forecasting models and performance metrics Mae, RMSE, and MAPE.
- Strong analytical problem-solving skills.
- Experience with data manipulation and model development.
- Knowledge of industry standard metrics (MAE, RMSE, MAPE, etc.)
- Familiarity with production-level modeling and evaluation workflows.
Responsibilities
- Research and evaluate statistical, machine learning, and persistence-based forecasting methods.
- Apply time series analysis to improve four class blending processes.
- Explore enhancements to solar PV forecast blending mechanisms and persistence strategies.
- Use programming tools (Python, NumPy, Pandas or R )for data manipulation and model development.
- Test and evaluate models using industry standard metrics (MAE, RMSE, MAPE, etc.)
- Collaborate with experienced staff on production-level workflows and model evaluation processes.
- Contribute to the development of advanced statistical approaches, persistence-based strategies, and the integration of AI and machine learning techniques to improve forecast accuracy.
Other
- Minimum Education Level: Senior
- Preferred Majors: Computer Science, Information Systems, Data Science
- Candidate must have completed at least the first year of college and be currently enrolled in a four year or graduate-level academic program.
- Candidates must have the authority to work in the US on a permanent basis, without requiring sponsorship.
- This employer will not sponsor applicants for work visas for this position (ex: H-1B, F-1/CPT/OPT, O-1, E-3, TN, J, etc.).
