Commodity Risk Manager – Aalborg, Denmark | Paragon Alpha

Commodity Risk Manager – Aalborg, Denmark

Permanent

Portfolio Management

Denmark

We are seeking an experienced Commodity Risk Manager to join a growing global risk function within a dynamic commodities trading environment. Reporting into senior risk leadership, this role plays a key part in providing a transparent, consistent, and forward-looking view of commodity risk exposure across the business.

The position offers the opportunity to work closely with trading teams and senior stakeholders, supporting the continued expansion of both financial and physical commodities activities across international markets.

Head of Risk Recruitment

Robert Murphy

rmurphy@paragonalpha.com

Key Responsibilities

  • Provide independent challenge and oversight of trading activities, including profit generation and risk allocation
  • Partner closely with front-office teams to support business growth while maintaining robust risk controls
  • Develop and enhance risk capabilities, including contributing to risk systems, analytics, and tooling
  • Build and maintain quantitative tools and libraries (e.g. Python) to support risk analysis and reporting
  • Communicate key risk exposures, trends, and insights clearly to senior management
  • Collaborate with risk colleagues across asset classes to share insights and ensure consistency in approach
  • Support the onboarding of new markets, products, and trading activities, including the development of appropriate risk frameworks
  • Take a hands-on approach to day-to-day risk monitoring, analysis, and reporting

Requirements

  • Significant experience (typically 7–10+ years) in commodities risk, trading, or quantitative roles
  • Strong understanding of physical commodities markets, particularly within energy (e.g. power and gas)
  • Experience with physical asset-related transactions and associated risk considerations
  • Familiarity with intraday trading, balancing mechanisms, and short-term risk management
  • Strong programming and data skills, including Python, SQL, and Excel
  • Experience with quantitative risk methodologies such as VaR and stress testing
  • Solid academic background in a quantitative discipline (e.g. mathematics, engineering, economics, finance, or similar)
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