🎯 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 Senior Quantitative Research Scientist to lead research initiatives for our foundational energy pricing models and help prove their quality with 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 software and quantitative research engineers. 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 5+ years of experience conducting applied ML research.
• You have a graduate degree in ML, statistics, or a related quantitative modeling field.
• You have a strong publication record in leading ML journals: NeurIPS, ICML, ICLR, etc.
• You have deep knowledge of applied math, probability, statistics and numerical algorithms.
• You have experience leading and mentoring quantitative/ML researchers and/or data scientists.
• You have experience researching and implementing machine learning models working with time series, graph, and spatial data.
• You have knowledge of optimization techniques in contexts beyond machine learning 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, 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.

Get in touch

Please apply at this link if you're interested.