Senior Model Risk Validator & Governance Lead

Sallie Mae

Arlington (VA)

Hybrid

USD 120.000 - 190.000

Vollzeit

Vor 4 Tagen
Sei unter den ersten Bewerbenden

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Benefits dieser Stelle

Competitive base salaries
Bonus incentives
Generous PTO & holidays
401k with employer match

Zusammenfassung

Sallie Mae is seeking a Manager, Model Risk to independently lead model validation activities across the enterprise. You will assess conceptual soundness, data quality, methodology, performance, and governance within the second line of defense.

You will prepare validation reports, challenge model developers, and collaborate with risk, finance, technology, and business teams to strengthen model risk practices while complying with regulatory expectations.

Qualifikationen

  • Bachelor's degree in mathematics, statistics, economics, finance, data science, engineering, or a related quantitative field.
  • 5+ years of direct experience performing model validation or closely related model risk oversight.
  • Proficiency in Python, R, SAS, SQL and related analytical tools.
  • Strong knowledge of quantitative analysis, model governance and model risk management principles.

Aufgaben

  • Independently plan and execute risk-based validations of new and existing models.
  • Lead validation engagements from scoping through final reporting.
  • Provide independent challenge to model developers, owners, and users.
  • Evaluate model performance monitoring, change management, and governance practices.
  • Prepare clear validation reports and present conclusions to stakeholders.

Tools

Python
R
SAS
SQL

Jobbeschreibung

Sallie Mae is seeking a Manager, Model Risk to independently lead model validation activities across the enterprise. You will assess conceptual soundness, data quality, methodology, performance, and governance within the second line of defense.

You will prepare validation reports, challenge model developers, and collaborate with risk, finance, technology, and business teams to strengthen model risk practices while complying with regulatory expectations.

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