Requisition ID: 96553
Join the Global Community of Scotiabankers to help customers become better off.
Enterprise Stress Testings (EST) mandate is to design and run the Banks stress testing program. We need a strong individual to help with credit stress testing the Banks portfolio. You will collaborate in building coherent, self-contained stress tests across geographies and products. This role has the potential for direct impact on strategic business decisions with stress testing as a decision-making tool by senior management in Global Risk Management as well as Finance executives and the Board.
What you’ll do in this role?
Develop and implement the credit risk stress testing models using technology platforms, primarily in R and Python
Implement models for projecting point-in-time values for probability of default/loss given default as a function of macro-economic variables
Conduct supplementary analysis on model results to provide insights into key drivers of credit losses in each stress scenario
Work with technology teams on data sourcing, technology frameworks to optimize computing efficiency
Assist senior management by supporting ad hoc stress analyses
Develop and implement regression models using highly developed technical skills for projecting point-in-time values of probability of default and loss given default for commercial and retail banking products as a function of macro-economic time series variables:
Collect and analyse historical data, choose appropriate model design/methodology, derive model parameters
Develop software code implementing the selected methodology to be run in the operational/production environment and generate risk parameter projections needed for calculating loan impairment charge
Effectively communicate and document model approaches, assumptions, model inputs used and modelling processes
What we’re looking for?
Advanced degree in Economics, Finance, Statistics, Mathematics, Engineering or other related quantitative discipline. Some knowledge of accounting preferred.
Experience in credit risk modeling related to probability of default and loss given default
Experience with R or Python is a requirement. Experience with sparklyr or pyspark is an asset
Advanced quantitative modeling skills (e.g., advanced statistical models, econometric models)
Strong computer skills in organizing and manipulating large amounts of data
Strong communication skills
Experience in banking with a focus on credit risk and credit products. Specific stress testing experience is desirable with working knowledge of IFRS9 accounting standards.
Knowledge of stress testing, and general knowledge of a banks financial metrics with a good understanding of credit products and provisions for credit losses (PCL)
Working knowledge of basic Linux or UNIX systems is desired. Experience with version control software (Git, SVN etc.) is an asset
This position is located in downtown, Toronto
Location(s): Canada : Ontario : Toronto
As Canada’s International Bank, we are a diverse and global team. We speak more than 100 languages with backgrounds from more than 120 countries. Our employees are committed to a superior customer experience and use the Banks six guiding sales practice principles to ensure they act with honesty and integrity.
At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.