Data Analyst - Forecasting and Optimization

Job summary

Company Description Cus*** (CES) is a global energy services and technology company that helps market participants operate, comply, and compete in deregulated electricity and natural gas markets.

Qualifications

• Bachelor's or Master's degree in Operations Research, Applied Mathematics, Electrical Engineering, Data Science, or equivalent
• 3+ years of hands-on experience in the electricity domain — energy trading, grid operations, market analysis, or a closely related quantitative role.
• Demonstrated experience formulating and solving optimization problems for real-world scheduling, dispatch, or resource allocation use cases
• Proficiency with at least one solver (Gurobi, HiGHS) and an optimization modelling library (Pyomo or similar)
• Hands-on experience building and deploying ML forecasting models for time-series data, preferably electricity prices or energy load
• Strong Python

Responsibilities

• You will work in a cross-functional team alongside software engineers and market operations specialists, with your models running in production and directly influencing real-world market outcomes.
• Design and implement optimization models to optimize energy bids across day-ahead and real-time electricity markets
• Translate electricity market rules, operational constraints, and grid conditions into mathematical formulations for the GridBOOST bid optimization engine
• Build and maintain machine learning pipelines for short-term electricity price forecasting, covering day-ahead, intraday, and ancillary service markets
• Engineer features from weather, demand, generation mix, and historical market signals to improve forecast accuracy
• Collaborate with software engineers to integrate models into production systems connected to real-time market data feeds
• Monitor live model performance, conduct systematic backtesting, and iterate on bid strategies and forecast models based on observed outcomes
• Analyse post-dispatch results and produce clear, actionable insights for trading and grid operations teams
• Track changes in regulatory frameworks, market mechanisms, and grid infrastructure that may affect model assumptions or bid strategies
• Document model logic, assumptions, and limitations to support auditability and knowledge transfer

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