We’re on a mission to improve the reliability, transparency, and efficiency of our energy systems, fostering a future with sustainable and abundant energy. To accomplish our aims, we’re leveraging state of the art statistical learning and convex optimization methods (AI) to build the financial rails of our future energy systems that will accelerate the deployment of clean energy resources.
We envision energy systems that are efficient, autonomous, resilient, and powered by 100% renewable energy.
Our founders (ex-Apple, Bluevine; ex-Affirm, Square, Google) are Stanford alumni with experience in complex systems, machine learning and structured finance. Our world-class investors, Maverick Ventures and Caffeinated Capital, are aligned to our policy objectives and platform vision.
We're headquartered in New York City, with a flexible approach to remote work.
Comity is looking for a Quantitative Researcher (FTRs) to help us develop market-leading power contract origination strategies with transmission congestion products.
You’ll study, design, and deploy models and optimization algorithms for transacting Financial Transmission Right (FTR) contracts in multiple Independent System Operators (ISOs). You’ll keep abreast of the latest research in quantitative finance and distributionally robust optimization, as well as help develop our data strategy and information systems by evaluating available data sources that can be integrated into our system to improve performance. As an early hire in this role, you will have broad impact and ownership over our algorithm design, research agenda, technology choices, and team culture.
You have 2+ years of experience applying quantitative methods to FTRs, PTP/UTC products, and/or congestion forecasting.
You have a strong working knowledge of one or more ISOs/RTOs.
You have an advanced degree in quantitative finance, computer science, statistics, machine learning, operations research, or a related quantitative field.
You have deep knowledge of applied math, probability, statistics and numerical algorithms, including knowledge of optimization techniques in contexts such as financial or electrical engineering, operations research, or economics.
You are adept at communicating mathematical concepts, analytical results, and data-driven insights to both technical and non-technical audiences.
You are a lifelong learner and empathetic teacher. We’re committed to the growth and development of our teammates. We work towards a shared understanding by listening with intent and holding open discussions because we know that's how we'll deliver quality results.
We believe strong foundations are more important than specific technical knowledge, but experience with any part of our data stack (Python, CVXPY, Snowflake) is a plus.
