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Quantitative Researcher in Portfolio Optimization

ComityNew York
On-site Full-time

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Experience Level

Experience

Qualifications

Experience in managing P&L as a quantitative portfolio manager. Deep understanding of applied mathematics, probability, statistics, and numerical algorithms. Knowledge of optimization techniques in finance. Strong coding capabilities in Python. Graduate degree in mathematics, statistics, machine learning, computer science, physics, or a related quantitative field. Excellent communication and teamwork skills.

About the job

About Comity

Comity builds financial frameworks for the next generation of energy systems. The team focuses on making energy more reliable, transparent, and efficient, with the long-term goal of fully renewable, autonomous, and resilient systems. Statistical learning and convex optimization are core to the approach.

Founded by Stanford alumni and professionals with backgrounds in complex systems, machine learning, and structured finance, Comity’s leadership brings experience from Apple, Bluevine, Affirm, Square, and Google. The company is supported by investors such as Maverick Ventures and Caffeinated Capital. Offices are in Chicago, New York City, and San Francisco.

Role Overview: Quantitative Researcher, Portfolio Optimization

This Quantitative Researcher will focus on portfolio optimization for Comity’s power trading strategies. The position is based in New York.

Early team members shape portfolio design, research direction, technology choices, and company culture.

What You Will Do

  • Develop information systems to monitor and guide Comity’s multi-strategy, market-specific autonomous trading systems.
  • Set acceptance criteria for new trading strategies.
  • Work with risk management on risk assessments and quantitative risk modeling.
  • Collaborate with software engineers, quantitative researchers, and finance to bring new assets to market and achieve business goals.

What We Look For

  • Experience managing P&L as a quantitative portfolio manager.
  • Strong background in applied mathematics, probability, statistics, and numerical algorithms.
  • Understanding of optimization techniques relevant to finance.
  • Proficiency in coding, especially Python.
  • Graduate degree in mathematics, statistics, machine learning, computer science, physics, or a related quantitative field.
  • Excellent communication and collaboration skills.

About Comity

Comity is committed to revolutionizing energy systems by enhancing their reliability, transparency, and efficiency. We employ advanced statistical learning and convex optimization methods to build the financial infrastructure for future energy solutions.

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