Job Summary
The ideal candidate will develop and implement advanced quantitative models to forecast energy market trends, prices, and risks. They will collaborate closely with traders, risk managers, and data scientists to enhance decision-making strategies.
Key Responsibilities
* Design and deploy machine learning algorithms to improve market predictions based on statistical modeling and time series analysis.
* Analyze large datasets related to renewable energy sources (wind, solar, hydro, etc.) and energy trading.
* Develop and optimize algorithms for power trading, hedging strategies, and asset valuation.
* Provide insights to stakeholders on energy price dynamics and market trends through effective communication of complex models.
Requirements
* Relevant experience in the renewable energy sector, specifically in power trading, electricity markets, or renewable asset modeling.
* Proficiency in programming languages such as Python, R, MATLAB, or C++.
* In-depth knowledge of statistical modeling, stochastic processes, and machine learning techniques.
* Hands-on experience working with energy market data, risk management, and optimization models.
* Familiarity with power markets, PPAs, battery storage, and renewable energy forecasting.
* Ability to work efficiently in a fast-paced, data-driven environment and effectively communicate complex ideas.