ENGIE Energy Marketing North America (EEMNA) is looking to advance its electricity market forecasting capabilities across timescales and regional markets to support trading, risk, and strategy functions by modeling hundreds of millions of data points daily through hybrid AI and physical system modeling. The goal is to enhance the performance, robustness, and scalability of their forecasting platform to influence trading decisions and operational strategies in dynamic power markets.
Requirements
- Proficiency with linear algebra and machine learning
- Proficiency with correlated uncertainty quantification and statistical analysis
- Proficiency with probabilistic thinking and evaluation
- Proficiency in a programming language such as Python (or similar) and SQL (or similar)
- Ability to combine theory and data to develop experiment driven methodologies
- Ability to articulate experimentation methods, results, and conclusions clearly
Responsibilities
- Analyze, experiment, develop models, and evaluate models to help the company gather business intelligence and predict electricity prices
- Work directly with the trading teams and Head of Market Analysis to create evaluation methodologies and assess quality of forecasts in terms of delivering clear signal for trading activities
- Collaborate with the team to expand forecasting capabilities across various timescales and U.S. markets including PJM, SPP, and CAISO
- Leverage data analysis to help identify areas for improvement of probabilistic price forecasts and develop experiments to help resolve and improve modeling efforts
- Work with the development team to develop production level code to backtest and run models at scale in the cloud
- Combine physical models with statistics and AI in creative ways to create models which are compute efficient while robust to extreme events and changes in the underlying system being modeled
- Work with and contribute to internal custom machine learning pipeline and physical model development using Python packages and in-house libraries
Other
- Minimum of a Bachelor’s degree in a Science, Engineering, or Mathematics field
- A minimum of ten (10) years working as a Data Scientist or a similar position
- This role is eligible for our hybrid work policy in our Houston, TX; Chicago, IL; and Broomfield, CO offices. For highly qualified candidates based in Pittsburgh, PA, a fully remote arrangement may be considered, provided the individual can travel to the Houston office for at least one week each month.
- Must be available to travel domestically up to 15% of the time and with the need for some overnight trips
- Must be willing and able to comply with all ENGIE ethics and safety policies
