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Careers at Fuse Energy
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Quant Trader

14 Aug 2024
London, UK

About the job

At Fuse, we're driven by a bold mission: to make renewable energy accessible for all. Our commitment to transparency, innovation, and sustainability fuels every step we take. We've raised $78 million from top-tier investors who share our vision, and now we're seeking a talented Commodity Analyst to join us in transforming the renewable energy landscape.


Your Role:

As a Commodity Analyst at Fuse, you will be at the forefront of building our power and gas analytical function, revolutionising how we understand and shape the renewable energy market. Your analytical prowess will be put to the test as you develop cutting-edge analytical tools tailored to the UK power and gas market. Your contributions will be essential to the development of our stack model, balance model, margin-based model, and price analysis tools.

Responsibilities:

  • Collaborate with the Trading Team to understand and address their requirements for the analytics platform.
  • Be integrated to the Trading Desk to develop analytical platforms and tools that meet business needs.
  • Contribute to the decision making process of the trading strategies.
  • Utilise Python programming language for data processing, analysis, and modelling in the Power and Gas market.
  • Conduct time series analysis, including data pre-processing, feature extraction, web scraping, model selection, and evaluation.
  • Visualise analysis results using tools like Metabase, creating clear and informative dashboards and reports.
  • Develop Position Balance, Market stacks and price forecast models.
  • Evaluate and monitor the accuracy and effectiveness of external price forecast models.
  • Develop analytics related to Power and Gas fundamentals, such as system margin analysis, spark and dark spread analysis, fuel cost adjustment forecast, maintenance program adjusted system availability, sensitivity and price visualisation tools.
  • Explore innovative ideas using advanced statistical analysis and machine learning techniques to improve forecast inputs and support long-term trading strategies.
  • Provide analytical support to the team in the UK.

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