Risk Analyst Intern

Xcel Energy is seeking a Risk Analyst Intern in Denver, CO, to join their Program Support team within the Integrated System Planning organization. The internship involves developing risk and uncertainty models, analyzing historical gas and power price forecast errors, and probabilistically modeling climate change impacts. Candidates should have experience with Python and knowledge in computer science or statistics. Benefits include paid time off, a pension, and a 401(k) plan, offering a chance to gain practical experience in the energy sector.
About the position

Are you looking for an exciting job where you can put your skills and talents to work at a company you can feel proud to be a part of? Do you want a workplace that will challenge you and offer you opportunities to learn and grow? A position at Xcel Energy could be just what you're looking for. Is it time to see how all those college courses translate to the real world? Are you ready to work alongside experienced professionals on real projects and issues? An internship at Xcel Energy will give you practical experience in the energy industry at a company that's committed to excellence, safety and environmental stewardship. The Risk Analyst Intern will be part of the Program Support team which is a part of the Modeling and Analytics group of the Integrated System Planning organization. The internship will largely be focused on supporting and developing risk/uncertainty models for the assumptions used by the planning modeling and analytics groups. ISP is a new Xcel Energy system planning organization designed to create mid to long term transmission, generation, distribution, and gas plans to help the company achieve its goals of a carbon free system by 2050. Examples of the projects that the role will be supporting include: Developing models to measure historical gas and power price forecast errors/uncertainty and applying the results to model the forecast stochastically by introducing defined uncertainty. This includes fitting a distribution to data, autoregressive correlation, demeaning, and removing seasonality to assess historical forecast errors. Supporting an initiative to probabilistically model climate change rates, working with historical weather data to modify it to match the current climate, generating additional weather scenarios, and combining the weather and climate scenarios to generate a probabilistic model of future weather. Supporting the integration of a Systemic Risk assessment project into the Project Planning and Execution process. Working with other probability assignments and Monte Carlo simulations and developing risk models as needed.

Responsibilities
• Support and develop risk/uncertainty models for planning modeling and analytics groups.
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• Develop models to measure historical gas and power price forecast errors/uncertainty.
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• Fit distributions to data and assess historical forecast errors.
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• Support initiatives to probabilistically model climate change rates.
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• Work with historical weather data to generate additional weather scenarios.
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• Integrate Systemic Risk assessment into Project Planning and Execution process.
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• Develop risk models using Monte Carlo simulations.

Requirements
• Experience with Python and/or other programming languages.
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• Knowledge of computer science/data science/statistics.

Nice-to-haves

Benefits
• Pension
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• 401(k) plan
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• Paid time off (PTO)
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• Holidays