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AnchorageAnchorageUnited States

Member of Global Risk Management, Quantitative Financial Risk

Develops quantitative tools and scalable Python pipelines for credit, market, and liquidity risk analysis at a digital asset firm. Requires 8+ years in quantitative finance, advanced degree, and expertise in stress testing and real-time risk monitoring.

Salary not listed
Remote8+ YOEData Engineering

About the role

Responsibilities

  • Design, build, and maintain quantitative analysis tools for credit, market, and liquidity risk assessment
  • Build scalable analytics pipelines in Python to automate reporting, data transformation, and real-time risk monitoring
  • Execute portfolio margin stress tests and scenario analysis under tight timelines, delivering actionable insights to stakeholders
  • Lead end-to-end development of quantitative analysis tools from problem definition through production deployment with minimal oversight
  • Run ad-hoc real-time analysis and deliver under pressure
  • Navigate ambiguous risk problems by selecting appropriate quantitative methods and articulating trade-offs to stakeholders
  • Collaborate closely with Trading, Sales, Compliance, Treasury, and Operations to ensure risk analysis and tools are embedded in business decisions
  • Monitor industry trends, regulatory developments, and emerging best practices in quantitative risk management
  • Translate complex quantitative concepts into clear, actionable insights for technical and non-technical audiences
  • Mentor junior team members on quantitative methods, analytics tooling, and professional development

Requirements

  • 8+ years of experience in quantitative finance, financial risk management, or a related quantitative discipline
  • Advanced degree (Master's or PhD) in a quantitative field
  • Proven track record of building quantitative analysis tools for risk management (credit, market, liquidity risk)
  • Deep expertise in risk monitoring and reporting, including experience building or operating real-time risk dashboards and producing executive-level risk reports
  • Experience with portfolio stress testing and scenario analysis in a professional setting
  • Experience working with large datasets and analytical tools to support risk analysis
  • Experience with regulators and regulatory exams

Nice-to-Haves

  • Experience with digital assets, crypto, or blockchain-related financial products
  • Understanding of operational risk and how it intersects with credit, market, and liquidity risk

Skills

PythonQuantitative AnalysisRisk ManagementStress TestingScenario AnalysisAnalytics PipelinesReal-Time DashboardsLarge DatasetsPortfolio MarginingFinancial Modeling
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