SESCO Enterprises, LLC is a proprietary commodities trading firm specializing in U.S. electricity markets. We leverage deep market insights and advanced quantitative analysis to drive results and contribute to the efficiency and reliability of the power grid.
We are looking for a Quantitative Researcher to join the research group at SESCO. You will join a team that is responsible for the effective creation, implementation, configuration, and maintenance of systems (software and environments) related to quantitative analysis and forecasting in the US Power Markets.
As a Quantitative Researcher, you will:
- Work to solve complex quantitative and technical problems in collaboration with a team of skilled quantitative researchers.
- Work in an iterative and highly dynamic environment that encourages collaboration and continuous improvement.
- Combine software development expertise with mathematical and optimization techniques to develop statistical and simulation-based models for forecasting.
- Create and maintain systems that integrate structured and semi-structured data into robust models used for scenario analysis and probabilistic outcomes.
At SESCO we embrace a hacker mindset to develop elegant, efficient, and impactful solutions to real-world challenges in energy 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.
- PhD in a technical discipline (e.g., Computer Science, Mathematics, Statistics, Physics, Economics, Engineering) or equivalent professional experience with progressive responsibilities.
- Strong foundation in linear algebra, probability, and statistics. A working knowledge of machine learning techniques preferred.
- Expertise in Python and related ecosystem (e.g., NumPy, Pandas, Numba, SciPy, Streamlit, etc.).
- Competency in standard software engineering practices.
- Proven ability to design and implement mathematical models and handle large, complex, and heterogenous datasets.
- Demonstrated success in transforming research into actionable insights and analysis.
- An emphasis on practicality and delivering working and robust systems.
- Understanding of origination, trading exposure, and financial implications and familiarity with power markets preferred but not required.
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