Sr Power Trader

We are looking for a Sr Power Trader with prior Day Ahead and FTR trading experience to join SESCO. You will work in a collaborative, cross-functional environment where personal outcomes are directly tied to the economics of trading decisions. The ideal candidate will have experience understanding power flow simulation outcomes and strong probabilistic decision-making skills to identify investment opportunities.

Role Responsibilities

As a Sr Power Trader, you will:

• Develop and deploy trading solutions and strategies to trade nodal congestion utilizing predictive information from powerflow simulations and scenario analyses.
• Assess risk profiles of trades and portfolios in a fundamental and systematic manner.
• Evaluate expected returns and make investment and capital allocation decisions based on probabilistic understanding of expected outcomes.
• Maintain thorough understanding of market structure and regulations while taking a research-based approach to market assessment and trading decisions.
• Develop quantitative approaches to portfolio management, risk management and expected value forecasting while working with a cross-functional team of traders, meteorologists and quantitative researchers.

Our Approach

At SESCO we embrace a hacker mindset to develop elegant, efficient, and impactful solutions to real-world challenges in electricity markets.

• Problem-Solving: We thrive on solving tough problems with creativity and rigor.
• Collaboration: We value a highly collaborative environment that blends diverse expertise.
• Innovation: Electricity markets demand innovative solutions to account for incomplete information and complex dynamics.

Qualifications

• Bachelor's degree in engineering or technical field (math, physics, economics). Advanced degree preferred.
• Minimum 2 years of trading experience with proven track record and demonstrated PNL history working for a power marketer or asset owner.
• Deep fundamental understanding of power flow simulation and electricity market structure and operations.
• Strong foundation in probability and statistics, with working knowledge of machine learning techniques preferred.
• Experience integrating quantitative analysis and techniques into fundamental trading strategies to optimize portfolio construction and outcomes.
• Experience managing and understanding risk empirically and assessing risk profiles for unprecedented events and tail outcomes.
• Demonstrated success in transforming research into actionable insights and analysis.
• Proficiency in Python and related ecosystem (e.g., NumPy, Pandas, Numba, SciPy, Streamlit).