Associate Director, Credit Modeling

2 weeks ago

Toronto, Canada Royal Bank of Canada Full time

**Job Summary**

The Associate Director, Credit Modeling & Methodology will support the model development team responsible for developing credit risk models and analytics tools used in the measurement of Expected Credit Loss, Provision for Credit Losses, Allowance for Loan and Lease Losses as well as for Stress Testing purposes.

**What is the opportunity?**

The Associate Director, Credit Modeling & Methodology will support the model development team responsible for developing credit risk models and analytics tools used in the measurement of Expected Credit Loss, Provision for Credit Losses, Allowance for Loan and Lease Losses as well as for Stress Testing purposes.

This role will assist the Director, Credit Modeling & Methodology in various model development initiatives spanning from data engineering (in order to construct the modeling data), development of modeling methodologies, model testing and implementation.

**What will you do?**
- Develop, document, and implement Credit Risk Models for use in IFRS-9, CECL, CCAR, Stress Testing (EWST, MST).
- Identify, communicate and troubleshoot modelling challenges, including related to data quality.
- Deliver sound quantitative methodologies and the results from employing them.
- Be agile in response to evolving model user requirements and competing priorities.
- Conduct model development work with strong attention to detail; validate material model assumptions and limitations, and identify potential errors before they arise.
- Present quantitative materials, concisely and accurately, internally as well as to key stakeholders.
- Support Business Review, Model Validation, User-Acceptance Testing, Internal Audit and External Audit or Regulatory Review of Credit Risk Models.
- Develop an organizational awareness, understanding process flows of data through model development through model users and impact to key business stakeholders.
- Provide comprehensive documentation as a key component of the work product.

**What do you need to succeed?**

**Must-have**
- Master’s Degree in quantitative field of study or equivalent
- Strong predictive modeling background and analytical problem solving skills
- Strong communication skills
- Effective in translating technical expertise into business language that drive insights

**Nice-to-have**
- Experience in credit risk modelling; familiar with financial credit products and relevant regulatory guidelines (e.g. IFRS9)
- Hands-on experience in SAS or similar tools; expertise with MS Office Suite.
- Expertise in navigating an Enterprise Data Warehouse, experience with Hadoop environments, Python, R or other tools

**What’s in it for you?**

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.
- A comprehensive Total Rewards Program
- Leaders who support your development through training and coaching
- Work with a dynamic, collaborative team with ability to make a difference

**Job Skills**

Competitive Markets, Consulting, Critical Thinking, Financial Instruments, Financial Regulation, Investment Risk Management, Long Term Planning, Quantitative Methods, Risk Management

**Additional Job Details**

**Address**:
RBC CENTRE, 155 WELLINGTON ST W:TORONTO

**City**:
TORONTO

**Country**:
Canada

**Work hours/week**:
37.5

**Employment Type**:
Full time

**Platform**:
GROUP RISK MANAGEMENT

**Job Type**:
Regular

**Pay Type**:
Salaried

**Posted Date**:
2024-02-16

**Application Deadline**:
2024-03-03

**I**nclusion** and Equal Opportunity Employment**

At RBC, we embrace diversity and inclusion for innovation and growth. We are committed to building inclusive teams and an equitable workplace for our employees to bring their true selves to work. We are taking actions to tackle issues of inequity and systemic bias to support our diverse talent, clients and communities.

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