Position Id
TDJP00042443
Location
Toronto ON
Job Type
Contract Full-Time

Position: Risk Analyst (Credit Risk/Model)

Duration: 12 months

Location: Remote for now and later Downtown Toronto

Job Description:

The position works closely with MMA teams, Retail Model Development (MD), Layer 6 (L6), Model Validation (MV), Model Risk Management (MRM), Line of Business Risk Management teams, and a number of external business partners with the following key accountabilities:

  • Assist in Model Monitoring code development, maintenance, and enhancements, including code reviews, as required.
  • Assist in the development and ongoing improvement of MMA’s Model Governance Framework. This includes monitoring activities relating to the execution and documentation of:
  • Model Performance Monitoring
  • Model Discrimination
  • Population Stability
  • Characteristic Analysis
  • Support multiple ad-hoc requests relating to model performance, working closely with partners in MV, MRM, MD and MMA.
  • Support Annual Model Reviews, ensuring concise and accurate quantitative analysis and documentation is delivered in a timely fashion for MD, MV, and MRM for review.
  • Support compiling material for executive committee meetings, status meetings, and dashboard reporting. Material is shared with internal and external stakeholders.
  • Support coordinating the collecting of evidence and closure of Audit and Regulatory findings.
  • Act as mentor and provide guidance and training to new hires.
  • Adhere to bank and industry best practices and standards for project management (PMLC).
  • Assisting in other areas within the Model Governance & Compliance space, as requested

Major programs:

  • In addition to BAU work, MMA will be focused on the following transformative initiatives:
    • SAS Grid DCJ project platform transformation

Job Requirements:

  • Strong working knowledge and preferably three or more years of extensive hands-on experience using SAS, SQL, or Python in the context of data manipulation, data mining, and statistical analysis.
  • Experience working in both operational and project environments
  • Strong quantitative skills with an advanced degree in math/statistics or related areas.
  • Good inter-personal skills to build and maintain productive working relationships with various business partners across the Bank and on different levels of organization.
  • Strong communication skills (both written and oral)
  • Ability to manage multiple initiatives and priorities, ensuring critical deadlines are met
  • Experience in model development or validation in retail credit risk would be an asset
  • Understanding of basic retail credit risk drivers would be an asset
  • Understanding of scorecard, machine learning, or PCL models would be an asset
  • Understanding of account management, adjudication, and collection strategies would be an asset
  • Understanding of regulatory programs such as Basel and IFRS9 would be an asset

Education and Accreditation:

  • Undergraduate degree in Mathematics, Statistics, Economics, Engineering, or similar disciplines. Postgraduate degree would be an asset.
  • PRMIA, GARP, CPA or similar accreditation is also considered an asset.
  • SAS, Python, or R certification would be considered an asset.

Must Have:

  • Strong working knowledge and preferably three or more years of extensive hands-on experience using SAS, SQL, or Python in the context of data manipulation, data mining, and statistical analysis.
  • Experience working in both operational and project environments
  • Strong quantitative skills with statistics or related areas
  • Good inter-personal skills to build and maintain productive working relationships with various business partners across the Bank and on different levels of organization.
  • Strong communication skills (both written and oral)
  • Ability to manage multiple initiatives and priorities, ensuring critical deadlines are met

NICE TO HAVE:

  • Experience in model development or validation in retail credit risk would be an asset
  • Understanding of basic retail credit risk drivers would be an asset
  • Understanding of scorecard, machine learning, or PCL models would be an asset
  • Understanding of account management, adjudication, and collection strategies would be an asset
  • Understanding of regulatory programs such as Basel and IFRS9 would be an asset
  • SAS, Python, or R certification would be considered an asset
  • PRMIA, GARP, CPA or similar accreditation is also considered an asset
  • Undergraduate degree in Mathematics, Statistics, Economics, Physics, Engineering, or similar disciplines. Postgraduate degree would be an asset

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