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Job Description
Responsibilities
Develop and implement quantitative models to support hedging strategies for retail energy supply
Analyze market data to optimize the performance of physical assets such as solar and wind farms
Conduct statistical and scenario-based modeling to inform trading and risk management decisions
Monitor power markets, pricing trends, and regulatory developments to identify risks and opportunities
Collaborate with engineering and operations teams to integrate models into day-to-day decision-making
Benefits
Competitive salary and an equity sign-on bonus
Biannual bonus scheme
Fully expensed tech to match your needs
Paid annual leave
Breakfast and dinner for office based employees
Develop and implement quantitative models to support hedging strategies for retail energy supply
Analyze market data to optimize the performance of physical assets such as solar and wind farms
Conduct statistical and scenario-based modeling to inform trading and risk management decisions
Monitor power markets, pricing trends, and regulatory developments to identify risks and opportunities
Collaborate with engineering and operations teams to integrate models into day-to-day decision-making
Benefits
Competitive salary and an equity sign-on bonus
Biannual bonus scheme
Fully expensed tech to match your needs
Paid annual leave
Breakfast and dinner for office based employees
Job Requirements
Requirements
1+ years of experience in quantitative modeling, data analysis, or a related role in energy, trading, or analytics
Strong proficiency in Python, with experience using libraries for data analysis, modeling, and visualization
Solid understanding of statistical modeling, optimisation, and analysis techniques
Experience working with time series or market data, preferably in energy or commodities markets
Strong problem-solving skills and the ability to translate complex data into actionable insights
1+ years of experience in quantitative modeling, data analysis, or a related role in energy, trading, or analytics
Strong proficiency in Python, with experience using libraries for data analysis, modeling, and visualization
Solid understanding of statistical modeling, optimisation, and analysis techniques
Experience working with time series or market data, preferably in energy or commodities markets
Strong problem-solving skills and the ability to translate complex data into actionable insights