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Develop and validate machine-learning forecasting and optimization algorithms for solar generation, power-market prices, battery operations, and bidding plans using market data.
Research and develop algorithms for solar power-generation forecasting, electricity-market price and imbalance forecasting, and optimization of battery operations and bidding plans.
Improve and validate time-series and quantile forecasting models; implement forecasting and optimization methods; backtest models using historical data; and evaluate them using accuracy and revenue metrics. Review papers and prior research and translate findings into implementations. Problem definitions, data, and evaluation metrics are prepared for the work.
Required qualifications include Python implementation experience in machine learning or mathematical optimization, code development using AI agents such as Claude Code or Codex, the ability to implement findings from papers and prior research, and the ability to communicate in Japanese. The stack includes Python, pandas or polars, scikit-learn or PyTorch as needed, BigQuery, GCS, and AI-agent tools.
This is an outsourcing contract. Remote work is available. Work is approximately 10 hours per week, with workload and working hours arranged according to circumstances.
Job details
About Bluefield Energy
Bluefield Energy is a Japan-based clean-energy company working on renewable power and energy-technology solutions.
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