Systematic Risk Manager | Paragon Alpha

Systematic Risk Manager

Permanent

Portfolio Management

New York

We are seeking an experienced Risk Manager to support a growing systematic trading platform. This individual will work closely with portfolio managers and quantitative teams to enhance risk oversight, portfolio construction insights, and performance evaluation.

Head of Risk Recruitment

Robert Murphy

rmurphy@paragonalpha.com

Key Responsibilities

  • Perform daily and intraday risk analysis across systematic trading portfolios
  • Partner with systematic portfolio managers and senior stakeholders globally
  • Review and challenge portfolio construction processes, including model architecture, simulations, and backtesting frameworks
  • Enhance manager selection and performance evaluation methodologies, with a focus on macro drivers and crowding dynamics
  • Develop and implement risk metrics tailored to shorter-term systematic strategies; build and maintain monitoring tools for portfolio managers
  • Contribute to the evolution of firm-wide risk analytics, reporting, and governance frameworks
  • Engage with senior leadership within the systematic business to support strategic decision-making
  • Participate in global risk discussions, providing insights and recommendations on risk-reward trade-offs

Requirements

  • Advanced degree (Master’s or PhD) in a quantitative discipline such as Mathematics, Physics, Computer Science, or Financial Engineering
  • 10+ years of experience in quantitative finance, ideally in risk management, portfolio management, or systematic trading within a bank, hedge fund, or trading firm
  • Strong programming skills (e.g. Python, C++, or C#)
  • Deep understanding of equity statistical arbitrage and factor-based models
  • Excellent communication skills, with the ability to engage effectively across technical and non-technical teams
  • Strong analytical and research capabilities, with a practical, solutions-oriented mindset
  • High attention to detail and ownership of deliverables, with a focus on data integrity and clarity of output

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