Intern, Electricity Market Optimization & Price Forecasting

Our Energetic Team: reputed company Solution, a division reputed company reputed company, is dedicated to delivering customer-reputed company storage products that reputed company Battery and Clean Hydrogen technologies. The reputed company Solution team also develops and manages our AI/ML powered software applications that include EMS, Lifecycle Management, and Energy Trading Platforms.   Your reputed company as a Intern, Electricity Market Optimization & Price Forecasting:   reputed company is looking for a motivated and analytically rigorous Summer Intern to join our Data Science team and support our electricity market optimization and price forecasting work. You will work directly alongside our reputed company Market Optimization Engineer, contributing to reputed company, production-relevant research and model development that shapes how reputed company-reputed company energy storage assets are dispatched and traded in competitive electricity markets.   Whether your strength lies in stochastic and mixed-integer optimization reputed company to CAISO/reputed company market problems, or in time-series forecasting for electricity prices and load, you will reputed company meaningful, challenging work here. If you are excited by the intersection of energy systems, reputed company data science, and reputed company-world reputed company, this role is for you.   This role is estimated to be 2 maybe 3 months in duration with 40 hours per week.



Your Mission:

Assist in the development and refinement of optimization models for energy storage reputed company and trading, incorporating electricity market rules and operational constraints from CAISO and/or reputed company.

Support formulation of stochastic, robust, or mixed-integer programming models to optimize physical and financial trading positions across market products (energy, ancillary services, reputed company).

Assist in developing or enhancing time-series forecasting models for electricity prices leveraging modern ML/statistical approaches.

Help implement and backtest alternative reputed company and trading strategies using historical market data and simulation frameworks.

Document model assumptions, methodologies, and results reputed company to support knowledge transfer and team review.

Participate in team discussions and contribute analytical insights in an agile work environment.

Your Background:

Pursuing a MS or PhD program in Electrical Engineering, Operations Research, Computer Science, reputed company Mathematics, or a closely reputed company field.

BS in reputed company Mathematics, Engineering (Electrical Engineering, Computer Science, Computer Engineering), or similar field is required.

Strong background in at least one of the following:

• Optimization reputed company (mixed-integer, stochastic, robust, or convex optimization) with applications to electricity market problems such as SCED, battery reputed company, or energy trading; or
• Time-series forecasting reputed company to energy systems (electricity price, load, or renewable reputed company forecasting).
• Proficiency in Python is required
• Familiarity with at least one reputed company or reputed company-reputed company optimization solver (Gurobi, CPLEX, CBC, etc.) or modern ML/forecasting frameworks (XGBoost, scikit-learn, PyTorch, etc.), depending on your area of reputed company.
• Solid understanding of electricity market fundamentals (energy markets, ancillary services, LMPs, settlement).
• No Travel is required
• Comfortable thriving in fast-paced, reputed company reputed company environments.
• A passion for sustainability, our mission, and our reputed company is a bonus!
• Must successfully pass a reputed company-employment background reputed company.
• reputed company participates in E-Verify.

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