Job Summary
As Associate Director, Enterprise Model Risk Management (EMRM) in our Group Risk Management (GRM) team, you will execute and document validation of the Bank's enterprise-wide credit risk rating systems and methodologies, with focus on Retail and Wholesale credit risk systems including wholesale, retail, and margin lending parameters (Probability of Default ("PD"), Loss given Default ("LGD") and Exposure at Default ("EAD")) used in both regulatory and economic capital.
Job Description
What is the opportunity?
As Associate Director, Enterprise Model Risk Management (EMRM) in our Group Risk Management (GRM) team, you will execute and document validation of the Bank's enterprise-wide credit risk rating systems and methodologies, with focus on Retail and Wholesale credit risk systems including wholesale, retail, and margin lending parameters (Probability of Default ("PD"), Loss given Default ("LGD") and Exposure at Default ("EAD")) used in both regulatory and economic capital.
You will develop and implement tools and methodologies required to underpin credit risk systems and parameters validation, and provide insightful robust analyses of credit risk systems including risk quantification validation.
What will you do?
- Perform ongoing Retail and Wholesale credit risk systems including parameters validations and provide insightful analysis of validation results
- Perform a wide range of data reconciliations and analyses, e.g. organizing, interpreting and analyzing data using various statistical techniques catered for validation purposes
- Execute and document appropriate quantitative and qualitative tests, review of the logic and conceptual soundness of credit risk rating systems, parameters and their inputs, accuracy, sensitivity, back testing, benchmarking etc.
- Develop and enhance approaches tailored to timelines and data availability, utilizing detailed or 80 / 20 solutions, and quantitative and / or qualitative approaches, as appropriate
- Deliver validation findings and elicit feedback and remediation action plans / solutions from model stakeholders
- Ensure project and risk objectives are accomplished within approved timeframes and complied with regulatory requirements, model risk policy and model operating standards
What do you need to succeed?
Must-have
Graduate degree in a quantitative discipline such as computer science / information system, statistics, econometrics and / or a relevant professional qualificationUnderstand various data system structures / processes and how they affect the inputs and outputs of credit risk validation dataAbility to communicate, verbally and in writing, complex concepts to a non-technical audienceStrong conceptual, analytical, detail-oriented and problem solving skillsStrong computer skills - SAS, SQL and Excel required; Python and MatLab are essentialAbility to work with large volume of data and various IT infrastructuresExecute with urgency while maintaining quality and efficiencyAdapt to shifting priorities, coupled with a sense of urgencyWorks well in teams2+ years of analytical and quantitative experience with a financial institution, in a related role such as a model developer / validator, data miner / analyst, or a risk managerNice-to-have
Ability to work in Unix, Teradata Data Warehouse and / or Hive Data Lake environmentsExposure to credit risk system design and Basel parameter estimation is an assetProactive learning and working skillsWhat'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 including bonuses and flexible benefits and competitive compensationLeaders who support your development through coaching and managing opportunitiesWork in a dynamic, collaborative, progressive, and high-performing teamJob Skills
Competitive Markets, Consulting, Critical Thinking, Financial Instruments, Financial Regulation, Investment Risk Management, Long Term Planning, Quantitative Methods, Risk Management