Quantitative Risk Modeler

1 week ago


Montreal, Quebec, Canada SGS Société Générale de Surveillance SA Full time

Societe Generale de Surveillance SA seeks a highly skilled Quantitative Risk Modeler to join our team in the Americas. As a key member of our Model Risk Management (MRM) team, you will play a crucial role in ensuring the accuracy and reliability of our risk models.

With a strong background in quantitative finance, statistics, and programming, you will be responsible for:

  • Model Development: Collaborate with cross-functional teams to design, develop, and maintain complex risk models using advanced statistical techniques and machine learning algorithms.
  • Model Validation: Conduct independent reviews of our risk models to ensure their soundness, accuracy, and effectiveness in managing risk.
  • Continuous Monitoring: Develop and maintain the continuous model monitoring (CMM) framework to assess model performance, identify potential issues, and recommend improvements.

To succeed in this role, you must have a deep understanding of risk management principles, regulatory requirements, and industry best practices. You should also possess excellent communication skills, both written and verbal, to effectively collaborate with stakeholders across different functions and geographies.

We offer a competitive salary of $120,000 - $180,000 per year, based on experience, plus benefits such as 20 vacation days, comprehensive health insurance, and a retirement savings plan.

About Our Company: Societe Generale de Surveillance SA is a leading provider of risk management solutions, serving some of the world's largest financial institutions. We are committed to delivering exceptional service, quality products, and innovative solutions that meet the evolving needs of our clients.

Qualifications: To be considered for this position, you should possess a Bachelor's degree in a quantitative field (Master's or PhD preferred), at least 3 years of experience in model development, validation, or a related field, and proficiency in programming languages such as Python, R, or C++. Familiarity with risk management software and tools is an asset.



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