Optimization Intern

What you might work on:

• Develop understanding of the rules for trading, battery, and flexible load participation in energy markets.
• Use our backtesting framework for simulating performance on historical data.
• Characterize risk-return trade-offs of different optimization-based approaches to asset operation.
• Adapt existing optimization formulations to new asset types.
• Develop predictive models that generate optimization inputs, such as predicting future energy prices
• Present results to the optimization team, Gridmatic as a whole, and Gridmatic clients.
• Write and review code, with attention to performance and readability.

You might be a good fit if you:

• Write robust code in Python.
• Have experience applying mathematical optimization to real world applications.
• Are familiar with optimization libraries such as CVXPY. 
• Are experienced with classical or deep learning based time series forecasting
• Have excellent communication and teamwork skills. 
• Have enthusiasm for learning. 
• Knowledge of the energy industry is a plus.
We recognize some candidates may hesitate to apply if they do not have all the listed skills. We encourage interested individuals to apply if they have relevant skills even if they do not have experience in every listed area.
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