Quantitative Researcher for Risk and Research Engagement

Comity

$100K — $150K *
Energy & Utilities
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Strong foundations in statistics, optimization, probability, machine learning, or applied mathematics
  • Experience developing quantitative models for portfolio analytics, risk management, or trading applications
  • Proficient in performance attribution, portfolio optimization, or systematic trading analytics
  • Comfortable influencing decision-makers in dynamic environments
  • Strong Python programming skills for building analytical tooling and handling large datasets
  • Intuitive understanding of markets and portfolio behavior
  • Ability to communicate complex quantitative insights to varied audiences

Responsibilities

  • Analyze U.S. power markets to identify opportunities and risks
  • Collaborate with Portfolio Managers and Risk Managers on portfolio construction and allocation decisions
  • Enhance backtesting, experimentation, and simulation infrastructure
  • Develop quantitative models for risk and performance analysis
  • Monitor portfolio P&L and exposures, providing actionable insights
  • Support decision-making under uncertainty using quantitative analysis
  • Work closely with engineering and leadership to scale trading and risk platform

Benefits

  • Collaborative and dynamic work environment
  • Opportunity to influence and shape portfolio and risk analytics
  • Exposure to senior leadership and decision-making processes
  • Access to state-of-the-art analytical tools and technologies
  • Possibility to work across major financial hubs in the U.S.
Full Job Description
The Role

This role sits at the intersection of portfolio management, quantitative research, and risk management. You will partner closely with Portfolio Managers, Risk Managers, and senior leadership to develop risk models, analyze power market dynamics, improve portfolio allocation decisions, and build the analytical infrastructure that supports our trading and risk platform.

You will work directly with decision-makers across the organization to deepen our understanding of market structure, portfolio behavior, and risk drivers in U.S. power markets. This role is highly collaborative, analytical, and hands-on, with significant opportunity to shape our risk and portfolio analytics capabilities as the platform scales.

In this role, you will:
  • Analyze U.S. power markets to identify market opportunities, portfolio risks, and drivers of performance
  • Partner directly with Portfolio Managers and Risk Managers to support portfolio construction, allocation decisions, and alpha research
  • Improve backtesting, experimentation, and simulation infrastructure to drive research outcomes
  • Develop quantitative models for risk analysis, scenario analysis, and performance attribution
  • Track and analyze portfolio P&L and exposures, delivering actionable insights to PMs and senior leadership
  • Support investment and risk decision-making under uncertainty by combining quantitative analysis and sound judgment
  • Collaborate closely with engineering, research, and leadership teams to scale Comity's trading and risk platform
We're excited about you because:
  • You have strong quantitative foundations in statistics, optimization, probability, machine learning, or applied mathematics
  • You have experience developing quantitative models for portfolio analytics, risk management, or trading applications
  • You have experience with performance attribution, portfolio optimization, or systematic trading analytics
  • You are comfortable influencing Portfolio Managers, Risk Managers, and senior stakeholders in fast-moving environments
  • You are a strong Python programmer with experience building analytical tooling and working with large datasets
  • You have strong intuition for markets, portfolio behavior, and risk under changing market conditions
  • You communicate quantitative insights clearly to both technical and non-technical audiences
  • You are intellectually rigorous and operationally resilient; you dig into messy problems and drive them to resolution

Nice to have
  • Experience in U.S. wholesale electricity markets, including virtual trading, congestion modeling, nodal pricing, or FTRs
  • Advanced degree in a quantitative discipline such as mathematics, statistics, computer science, engineering, physics, or economics
Location

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

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