Gas, Power Data Science Sr Adv_TRGD
Listed on 2026-10-05
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IT/Tech
Data Scientist, Machine Learning/ ML Engineer
HOUSTON, United States, 77056 | San Francisco, United States, 94111
ENGIE ENERGY MARKETING NA, INC.
Digital / IT / Data
Permanent
Full - Time
What You Can Expect
Data is at the heart of ENGIE’s mission to provide sustainable energy clients with superior insights that enable strategic, actionable trading and dispatch decisions. Every day, the Global Market Analysis team forecasts hundreds of millions of electric grid data points using a combination of physical modeling, statistics, and artificial intelligence.
As a Senior Data Scientist, you will play a critical role in advancing ENGIE’s forecasting platform across multiple markets and time horizons. This position will focus on short-term power price forecasting and will work closely with battery trading and optimization teams to improve forecast accuracy, drive profitability, and support operational decision-making. The role requires strong analytical thinking, intellectual curiosity, and the ability to bridge physical system understanding with advanced computational modeling
- Analyze, develop, test, and improve forecasting models used to predict electricity prices and support trading decisions
- Own and enhance short-term forecasting workflows that generate updated forecasts throughout the day
- Partner closely with trading and optimization teams to evaluate forecast performance and determine the impact of forecast quality on trading profitability
- Expand forecasting capabilities across multiple U.S. power markets, including ERCOT, PJM, SPP, and other emerging opportunities
- Design and execute experiments to identify sources of forecast error and improve probabilistic forecasting performance
- Leverage statistics, machine learning, AI, and physical system models to build robust forecasting solutions
- Develop production-level Python code that supports large-scale model training, backtesting, and deployment in cloud-based environments
- Contribute to internal machine learning infrastructure, forecasting pipelines, and AI-enabled development tools
- Collaborate with a multidisciplinary team of experts in power systems, weather analytics, artificial intelligence, and market modeling
What You’ll Bring
- Bachelor's degree in Data Science, Computer Science, Engineering, Mathematics, Physics, Statistics, or another quantitative STEM discipline.
- Minimum 5 years of experience working as a Data Scientist, Machine Learning Engineer, Quantitative Analyst, or similar role.
- Minimum 10 years of relevant work experience
- Advanced proficiency in Python and experience developing production-quality code.
- Strong knowledge of machine learning, statistical analysis, uncertainty quantification, and predictive modeling.
- Strong understanding of linear algebra, probability, and experimentation methodologies.
- Experience working with large datasets and building scalable analytical workflows.
- Ability to communicate technical concepts, experimental results, and recommendations clearly to technical and business stakeholders.
- Demonstrated critical thinking, problem-solving, and analytical capabilities.
- Strong attention to detail and commitment to delivering high-quality solutions.
- Team-oriented mindset with a collaborative approach to problem solving.
- This role is eligible for our hybrid work policy; a minimum of 3 days working in the office per week is required
- Must be available to travel domestically or internationally up to 10% of the time
- Must be willing and able to comply with all ENGIE ethics and safety policies;
Compensation
Salary Range: $135,000 – $206,885 USD annually
This represents the average expected pay range for a qualified candidate.
ENGIE complies with all federal, state, and local minimum wage laws. Actual salary offered may vary depending on geography, experience, education, internal pay…
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