Quantitative Researcher for Monetization

Comity; New York (NY); On-site; USD 100,000 - 140,000; Full time

Job summary

A forward-thinking energy firm is seeking a Quantitative Researcher for Monetization to design and operate autonomous strategies that derive economic value from information and energy systems. The ideal candidate has over 5 years of experience in applied stochastic optimization within financial or electrical engineering, and is proficient in Python. Located in New York, the role involves identifying market opportunities and leveraging machine learning models to optimize performance. Join us and be part of a team committed to sustainable energy solutions.

Qualifications

• 5+ years of design, research and development experience in industry.
• Deep understanding of energy or other commodity or financial markets.
• Experience developing and monitoring machine learning models.

Responsibilities

• Identify and prioritize market opportunities by expected value and difficulty.
• Architect autonomous strategies end to end.
• Optimize strategy performance leveraging metadata.

Skills

Applied stochastic optimization

Probability theory

Machine learning models

Python programming

Job 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.

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.

The Role

Comity is looking for a Quantitative Researcher for Monetization to help us design, deploy, and operate autonomous, systematic strategies that realize economic value from our future information (forecasts) and energy systems models, under real-world market constraints. You’ll

• Identify and prioritize market opportunities by expected value and difficulty
• Architect autonomous strategies end to end — model, forecasts, market actions
• Optimize strategy performance by leveraging metadata to augment bidding decisions
• work end-to-end from information development to production-ready code if resources are otherwise occupied

We’re excited about you because:

• You have applied stochastic optimization to problems in financial or electrical engineering, operations research, or economics.
• You have conceptual fluency with probability theory and good taste for shaping and managing distributions.
• You have 5+ years of design, research and development experience in industry.
• You have a deep understanding of the structure of energy or other commodity or financial markets and their dynamics.
• You are experienced and comfortable developing and monitoring machine learning models.
• You are a skilled programmer in Python.

More importantly —

• You are extraordinarily driven — you’re relentless in getting research artifacts into production and willing and capable to work end-to-end (forecasts, models, optimization, production-quality code) when supporting resources are contended.
• You love winning — while you prioritize well, there’s no task too tedious if it drives performance.
• You are predisposed to collaboration — we maintain a highly open and discursive environment which rewards the refinement of everyone’s ideas and requires genuine curiosity.

Location

We have hubs in New York, Chicago, and San Francisco.

At Comity, we seek to recruit, develop, and retain the most talented people from a diverse candidate pool. Our priority is to ensure that all applicants are provided with fair and equal access to employment opportunities. Recruiting and hiring decisions are made without regard to race, color, religion, sex, national origin, age, disability, or any other class protected by law.