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MET Group

Long-Term Power Analyst

Posted Updated
Discussion
  • Design, configure and operate fundamental stack models and reduced modelling configurations across European markets, with a focus on mid/long-term horizons
  • Develop and implement structural, weather and targeted sensitivity scenarios
  • Calibrate, benchmark and quality-assure model inputs, assumptions and outputs, and drive improvements in model robustness
  • Deliver recurring core model outputs and improve automation, post-processing and reporting of model runs
  • Interpret price, generation, capture, curtailment, storage, gas / CSS and network results and frame them in their commercial context
  • Develop long-term modelling architecture and methodology, including benchmarking of detailed and reduced configurations and alternative modelling approaches
  • Support desk-focused forward analysis and maintain consistency and calibration between near-/mid-term market views and the long-term modelling framework
  • Work closely with Long-Term Researchers to implement researched system-development assumptions in consistent model scenarios
  • Contribute to asset valuation, strategic analytics and longer-term scenario work
  • Cooperate closely with traders, gas analysts, Long-Term Researchers, Data Engineering and other relevant stakeholders
  • At least 5 years of relevant experience in power-market analysis, fundamental modelling or cross-commodity analysis, ideally within the energy trading / commodities sector
  • Power-market fundamental stack-modelling experience, ideally including forward-horizon or scenario-based modelling
  • Bachelor’s degree in Finance, Economics, Engineering, Mathematics, or a related field
  • Strong analytical and quantitative skills, including statistical / econometric analysis and model validation
  • Strong understanding of European power-market dynamics across supply, demand, storage, fuel economics and transmission constraints
  • Excellent presentation and communication skills
  • Ability to explain complex modelling results clearly and translate analysis into commercially relevant views
  • Coding skills in Python and SQL are an advantage

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