Quantitative Researcher - Chicago, United States - Comity

Description

Why we exist:

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.


Who we are:

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.


The Role:

Comity is looking for a Quantitative Researcher (Power) to help us build our foundational energy pricing models and market-leading power contract origination strategies.

You'll study, design, and deploy models and optimization algorithms for participating in wholesale energy markets, and you'll scale them in partnership with our engineering team.

You'll keep abreast of the latest research in machine learning and distributionally robust optimization, as well as help develop our data strategy 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 model design, research agenda, technology choices, and team culture.

We're excited about you because:

• You have 3+ years of experience conducting applied quantitative finance or machine learning research.
• You have one or more years of experience in the electricity and energy domain.
• You have an advanced degree in computer science, statistics, machine learning, operations research, or a related quantitative field.
• You have deep knowledge of applied math, probability, statistics and numerical algorithms.
• You have experience working with time series, graph, and spatial data.
• You have 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 datadriven insights to both technical and nontechnical 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, SQL, PyTorch, CatBoost) is a plus.

Location:

We're headquartered in New York City, with a flexible approach to remote work and work from home.