RBC
Associate Director, Enterprise Model Risk Management
TORONTO, Ontario, Canada · Director · Full-time
Sponsorship not specifiedDetected 5 hours ago
PythonExpressGitMachine LearningDeep LearningSparkData ScienceData VisualizationStatisticsCommunicationRisk ModelingHadoop
> stay_score
odds of building a lasting career here
16Unrated
Cap-exempt (no lottery)0
Sponsors this role0
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
No strong sponsorship signal in the public record yet. In the full product we resolve the exact legal entity and show its filing history with a confidence score — treat as unverified until then.
Lottery odds assume a STEM candidate.
Personalize to your clock →> community_outcomes
No reports yet — be the first to help the next applicant.
About the role
- Job Description What is your opportunity?
- Employ various quantitative and qualitative techniques to review, test, replicate, challenge, benchmark and assess credit risk models.
- Ensure model validations are planned and completed in accordance with timelines established in the Enterprise Model Risk policy based on each model's materiality and uncertainty rating.
Responsibilities
- Perform initial review and validation of newly developed credit models and make recommendations supporting use of the model.
- Develop comprehensive reports summarizing key observations, conclusions, and recommendations in support of completed model validations.
- Strategic thinker with superior interpersonal, verbal and written communication skills and with strong consensus-building skills.
- We thrive on the challenge to be our best, thinking progressively to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper.
Requirements
- Solid understanding of data extraction and data mining, proficiency in SQL.
- Post graduate degree in a quantitative field of study (i.e. PhD, Master of Mathematical Finance, Statistics, Computer Science, Applied Mathematics, Data Science or comparable).
- A strong understanding of retail credit risk modeling theories, principles and industry best practices.
- A strong understanding of RBC's policies, procedures, systems, risk appetite, risk tolerance, strategies and the overall role of risk management within RBC is a definite asset.
- Experience with Hadoop, Spark, object storage solutions.
- Experience with version control tools (git).
Benefits
- Hands-on experience with artificial intelligence / machine learning modeling techniques (deep learning, XGboost) as well as logistic regression modeling techniques.
This listing is sourced directly from RBC's careers page and normalized into a canonical job model.