Quantitative Risk Modeling & Research Analyst

Selby Jennings Ltd

  • Indianapolis, IN
  • 4 days ago

    Highlights

    This individual will be responsible for quantitative research, model development, implementation, validation support, and ongoing enhancement of credit, valuation, and risk models used across the organization. Develop, implement, and maintain models related to credit risk, valuation, collateral analysis, and loss forecasting.

    Numbers & Facts

    LocationIndianapolis, IN

    Description

    A financial institution is seeking a Quantitative Risk Modeling & Research Analyst to join its Enterprise Risk team. This individual will be responsible for quantitative research, model development, implementation, validation support, and ongoing enhancement of credit, valuation, and risk models used across the organization.

    Responsibilities:

    • Conduct quantitative research and evaluate emerging methodologies to improve risk measurement and model performance
    • Develop, implement, and maintain models related to credit risk, valuation, collateral analysis, and loss forecasting
    • Perform model testing, calibration, monitoring, and statistical analysis to assess model effectiveness
    • Create and maintain model documentation, methodologies, assumptions, and governance materials
    • Partner with risk, audit, technology, and business teams to support model development and analytics initiatives
    • Support model validation activities, regulatory reviews, and remediation efforts
    • Lead model enhancements and contribute to broader research and analytics initiatives

    Requirements:

    • Master's or PhD in Statistics, Mathematics, Financial Engineering, Economics, Operations Research, or a related quantitative field
    • 2-5 years of experience in quantitative research, model development, risk analytics, or related functions within financial services
    • Strong skills in SQL, Python and/or C++
    • Experience applying statistical and analytical techniques to financial or risk-related problems
    • Familiarity with model governance and validation

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