Minimum qualifications:
- Bachelor's degree in a technical field, or equivalent practical experience.
- 2 years of experience in quantitative modeling within the energy industry, with a focus on renewables, data centers, or gas plants.
- 2 years of experience in program management.
- 2 years of experience in Python programming.
- Experience with optimization techniques and tools.
- Experience building and implementing Monte Carlo simulation engines for risk assessment and forecasting.
- Knowledge of energy trading, risk management, statistical modeling techniques, and data analysis methods.
- Deep understanding of energy market fundamentals, including electricity markets, renewable energy integration, and gas market dynamics.
- Excellent communication and presentation skills, with the ability to explain complex technical concepts to a non-technical audience.
- Proficiency in Python programming and relevant libraries (e.g., NumPy, Pandas, SciPy, Scikit-learn).
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About the job
We are seeking a highly skilled and motivated Energy Quantitative Modeler to join our growing team. In this role, you will be responsible for developing and maintaining sophisticated quantitative models to analyze and forecast energy market dynamics, with a focus on renewable energy, data centers, and gas plants.
The US base salary range for this full-time position is $122,000-$178,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
Responsibilities
- Develop and implement quantitative models in Python to simulate and forecast energy market behavior, including electricity prices, generation, and demand.
- Build and maintain models for renewable energy assets (solar, wind), data centers, and gas-fired power plants, considering their unique operational and economic characteristics. Design and implement Monte Carlo simulation engines to assess risks and uncertainties associated with energy projects and market conditions.
- Conduct data analysis and statistical modeling to identify trends, patterns, and drivers of energy market dynamics. Collaborate with cross-functional teams (e.g., trading, operations, strategy) to understand business needs and translate model outputs into actionable insights.
- Communicate model results and recommendations clearly and effectively to both technical and non-technical audiences.
- Contribute to the improvement of existing models and the development of new modeling methodologies. Ensure model accuracy, reliability, and documentation.