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Mid-level generalist title, 3–6 years requirement, and metro location increase applicant density.
Core optimisation and Python skills are transferable, but energy-market knowledge provides useful domain advantage.
Explicit 4+ years plus mandatory Python and optimisation/Gurobi skills create strict filters.
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Develop, test, and maintain Python-based mathematical optimisation models simulating energy asset behaviour and revenue in US wholesale electricity markets.
Design, refactor, and maintain high-quality software and data pipelines supporting investment decision-making in energy markets.
Conduct technical testing, maintain documentation, and leverage AI tools to improve development and debugging efficiency.
Bachelor's degree with 4+ years or Master's degree with 2+ years in Electrical Engineering, Computer Science, Applied Mathematics, Operations Research, or related field.
Expert proficiency in Python with clean, production-quality coding experience.
Strong experience with mathematical optimisation tools such as Pyomo, GurobiPy, or LP/MIP solvers.
Work Experience Required: 4+ years (Bachelor) or 2+ years (Master) relevant experience.
Experienced in developing optimisation models for energy assets, preferably in wholesale electricity markets.
Proficient in advanced Python development and mathematical optimisation frameworks with production deployment experience.
Familiar with cloud technologies (AWS), machine learning model deployment, and AI-powered developer tools to enhance productivity.