Credit Risk Modelling Senior Associate

PwC Canada

Base: $73,400 - $122,400; bonus/equity: variable i...
Hybrid
Retail and wholesale credit risk modeling
Ifrs9 and cecl allowance modeling
Ai/ml/genai model development and validation
PwC Canada is seeking a Credit Risk Modelling Senior Associate to join their Financial Services Risk & Regulatory Group. The role focuses on developing and validating credit risk models, including those powered by AI/ML technologies, while fostering collaboration and client relationships in a hybrid work environment

Job Summary

  • This role offers the opportunity to help financial institutions rethink their approach to risk by developing distinctive strategies and creating capabilities.
  • The team focuses on predictive modeling needs including expected credit loss measurement under IFRS9 and CECL frameworks as well as capital measurement.
  • PwC Canada is committed to cultivating an inclusive, hybrid work environment with competitive compensation and comprehensive benefits.

Matching Summary

Match Score: 85

PwC Canada is seeking a Credit Risk Modelling Senior Associate to join their Financial Services Risk & Regulatory Group. The role focuses on developing and validating credit risk models, including those powered by AI/ML technologies, while fostering collaboration and client relationships in a hybrid work environment.

Salary

Base: $73,400 - $122,400; Bonus/Equity: Variable incentive pay programs available; Benefits: Competitive compensation package and inclusive benefits

Skills & Requirements

Must-have

  • Retail and wholesale credit risk modeling
  • IFRS9 and CECL allowance modeling
  • AI/ML/GenAI model development and validation
  • Python, R, SQL, SAS programming proficiency
  • Basel regulatory capital and stress testing

Nice-to-have

  • Vertex AI or Azure AI platform experience
  • Climate risk modeling expertise
  • PRM, FRM, or CFA designation
  • Thought leadership and white paper writing
  • Client proposal development skills

Key Requirements

  • Master's degree in Statistics, Mathematics, Physics, Engineering, Financial Engineering, or Data Science
  • Proficient experience in financial services risk practices and credit risk modeling
  • Proven ability in quantitative credit risk measurement methodologies

Work Rights

Not specified

Tailored Resume

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