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Sr. Quantitative Model Risk Analyst

$120k

Insight Global

Senior Quantitative Model Risk Analyst

Location: Cincinnati, OH

Schedule: Hybrid, three days per week onsite

Employment Type: Full-time

Salary: Up to $120,000 per year

About the Role

We are looking for an experienced Senior Quantitative Model Risk Analyst to help evaluate the financial and market-risk models used by a banking organization. Rather than developing models for day-to-day business use, you will independently review models created by other teams to determine whether they are accurate, reliable, appropriately designed, and compliant with regulatory expectations.

This role is especially well suited for someone with experience in model risk management, market risk, asset liability management, interest rate risk, treasury risk, or financial model validation . You will work with quantitative teams and business leaders while translating complex findings into practical recommendations.

What You’ll Do

  • Independently validate financial and market-risk models used for pricing, forecasting, risk measurement, and business decisions.
  • Review model assumptions, methodologies, data, calculations, implementation, and ongoing performance.
  • Identify weaknesses, limitations, biases, or gaps and recommend improvements or alternative approaches.
  • Evaluate models related to areas such as:
  • Asset liability management, or ALM
  • Interest rate risk, or IRR
  • Economic value of equity, or EVE
  • Net interest income, or NII
  • Mortgage valuation and prepayment
  • Derivatives and financial instruments
  • Liquidity risk
  • Fixed-income analytics
  • Prepare clear model-validation reports that document testing, findings, risks, and recommendations.
  • Support the organization’s model-risk framework, including model inventory, change management, governance, and ongoing monitoring.
  • Partner with model developers, treasury professionals, risk leaders, and other stakeholders.
  • Help maintain compliance with applicable model-risk regulations and guidance.
  • Provide guidance and mentorship to junior team members.
  • Identify opportunities to improve, automate, and streamline model-validation processes.

What We’re Looking For

  • At least five years of experience in model risk management, model validation, market risk, quantitative risk, or a closely related field.
  • Experience validating or developing financial models within a bank, financial institution, consulting firm, regulatory agency, or rating agency.
  • Direct exposure to models used for pricing, risk measurement, forecasting, valuation, or decision-making.
  • Strong understanding of financial or market risk, particularly within banking or capital markets.
  • Experience using Python, R, SAS, MATLAB , or a similar quantitative tool for model testing and analysis.
  • Bachelor’s degree in finance, financial engineering, economics, mathematics, statistics, or a related quantitative discipline.
  • Ability to clearly explain technical findings, model limitations, and business risks to both technical and nontechnical audiences.
  • Strong written communication skills, particularly when preparing formal validation reports.

Preferred Qualifications

  • Master’s degree or Ph.D. in a quantitative or financial discipline.
  • Experience with ALM, interest rate risk, treasury, market risk, mortgage, derivative, liquidity, or fixed-income models.
  • Experience working within an established banking model-risk management framework.
  • Familiarity with regulatory expectations for financial-model governance and independent validation.

Why Consider This Opportunity?

  • Take ownership of complex, high-impact model validations.
  • Focus on financial and market-risk models rather than primarily credit-risk models.
  • Work with quantitative, treasury, risk, and business stakeholders across the organization.
  • Help influence how models are governed and used for important financial decisions.
  • Join a hybrid team with a consistent three-day onsite schedule in Cincinnati.

Vacancy posted 1 hour ago
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