2027 Summer Intern - Load and Weather Risk Analyst

Midcontinent Independent System Operator (MISO)•Carmel, IN

1d•Onsite

About The Position

As our Load and Weather Risk Analyst Intern, you’ll contribute to Operations Risk Management’s mission of accurately forecasting load and quantifying risk that drives decisions in managing energy across the transmission grid — helping ensure efficient generation dispatch, adequate energy supply, and stable prices for millions of people across the region. You’ll gain hands-on experience with developing or enhancing load probability forecasting models, identifying and building models that assess renewable generation risk, including ramp periods, using historical and real-time weather and load data, and automating and modernizing legacy forecasting tools and scripts using Python and SQL. A good day in this role means accurately forecasting load and quantifying and communicating the risk that drives decisions in managing energy across the transmission grid. Accurate weather forecasting reduces uncertainty and lowers the risk associated with renewable generation and load forecasting. You’ll know you’re making an impact when your forecasts and risk analysis help drive efficient generation dispatch, an adequate energy supply, and stable prices. This role sits at the intersection of weather science, power systems, and financial risk — few teams in the energy industry blend meteorology with grid operations and market risk management the way this one does. You’ll gain exposure to how forecasting accuracy directly shapes operational decisions and market outcomes across MISO’s footprint.

Requirements

Proficiency in Python and SQL for data analysis

Nice To Haves

Coursework or experience in atmospheric science, physics, economics, or business
Prior meteorological internship experience
Familiarity with interpreting weather models and knowledge of renewable and thermal generation, transmission grids, and energy distribution

Responsibilities

Developing or enhancing load probability forecasting models
Identifying and building models that assess renewable generation risk, including ramp periods, using historical and real-time weather and load data
Automating and modernizing legacy forecasting tools and scripts using Python and SQL