Hybrid Senior Data Scientist - Power & Gas Forecasting

ENGIE North America Inc.; Houston (TX); Hybrid; USD 135,000 - 207,000; Full time

Benefits offered by this job

Health benefits

Hybrid work policy

Competitive bonus plan

401(k) retirement plan match

Job summary

ENGIE North America Inc. seeks a Gas, Power Data Science Sr Adv to advance forecasting across multiple US power markets. You will focus on short-term price forecasting and work with battery trading and optimization to boost profitability, deploying production-grade Python workflows in cloud environments.

The role demands deep ML knowledge, statistical rigor, and collaboration across power systems and market modeling teams to deliver robust insights for trading decisions.

Qualifications

• Bachelor's degree in a quantitative STEM field.
• Minimum 5 years as a Data Scientist, ML Engineer, Quantitative Analyst, or similar.
• Advanced Python and production-quality code development.

Responsibilities

• Analyze, develop, test, and improve forecasting models for electricity prices.
• Own and enhance short-term forecasting workflows updated throughout the day.
• Partner with trading/optimization teams to assess forecast impact on profitability.
• Expand forecasting across US power markets (ERCOT, PJM, SPP, etc.).
• Design experiments to identify forecast error sources and improve probabilistic forecasts.
• Leverage ML, AI, and physical models to build robust forecasting solutions.
• Develop production-grade Python code for model training, backtesting, deployment in cloud environments.
• Contribute to ML infrastructure, forecasting pipelines, and AI tools.
• Collaborate with power systems, weather analytics, AI, and market modeling experts.

Skills

Python

Machine learning

Statistics

Experimentation

Data analysis

Education

Bachelor's degree in a quantitative STEM field

Tools

Python

SQL

Pandas

scikit-learn

Job description

ENGIE North America Inc. seeks a Gas, Power Data Science Sr Adv to advance forecasting across multiple US power markets. You will focus on short-term price forecasting and work with battery trading and optimization to boost profitability, deploying production-grade Python workflows in cloud environments.

The role demands deep ML knowledge, statistical rigor, and collaboration across power systems and market modeling teams to deliver robust insights for trading decisions.