Quantitative Risk Analyst

3 weeks ago

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

About the Role:

The Risk Management Department at SGS Société Générale de Surveillance SA contributes to the sustainable growth of the organization through its expertise, understanding of risks, and risk management techniques. The department's mission is to independently analyze, assess, manage, and monitor risk-taking activities with the objective of achieving the best possible outcome for the bank. The department oversees the enterprise, strategic, credit, market, liquidity, operational, model, and other risks of the corporate and investment banking business activities.

Responsibilities:

  • The design of the model risk management system, as well as its consistency, integrity, and compliance with regulatory provisions.
  • Managing the model approval process within the scope of the role.
  • Monitoring of the models' performance, effectiveness of the model risk management framework, and the model business environment on an ongoing basis, and risk management of the model portfolio, ensuring adherence to regulatory requirements.

Key Responsibilities:

  • Independently assess model design and conceptual soundness by conducting quantitative analyses, statistical tests, and developing challenger models for benchmarking.
  • Verify the quality and consistency of data inputs, transformations, and outputs, using advanced statistical techniques to address complex datasets.
  • Review and replicate model architecture to ensure computational accuracy and correct implementation.
  • Perform backtesting, benchmarking, and sensitivity analysis to evaluate model performance and accuracy.
  • Regularly assess model performance, recommending adjustments or redevelopment based on changes in market conditions, products, or clients.
  • Evaluate governance aspects, including change management and ongoing monitoring, and assess overall model risk.
  • Draft detailed validation reports and communicate findings to stakeholders, including management and business partners.

Requirements:

  • Bachelor's degree in a quantitative field such as Mathematical Finance, Financial Engineering, Statistics, or STEM, or Master's or PhD preferred.
  • Minimum 3 years in model development, validation, or a front-office quant role; fewer years accepted with a PhD.
  • Strong programming skills in Python, R, C++, or similar, with advanced knowledge of statistics, econometrics, and machine learning.
  • Experience working with large datasets and quantitative analysis.
  • Excellent written and verbal communication skills for working with both technical and non-technical staff.
  • Familiarity with model risk management practices and regulatory requirements.

Languages: English and French.

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