AVP - Model Development
Within Risk Methodology, the Treasury Modelling and Analytics (TMA) team partners with the Treasury and Finance organizations to provide modeling and analytical problem solving for important regulatory and internal strategic initiatives - such as Capital Stress Testing, Risk in the Banking Book, and Strategic Planning.
The role holder will have the opportunity to gain a fundamental understanding of the Bank's risk and capital processes including model projection methodology across B/PPNR, credit risk, market risk, operational risk, and RWA as well as an enterprise-level perspective of CCAR, Interest Rate Risk, and Strategic Planning activities.
Your key responsibilities:
Task: Very complex analysis, evaluation & decision-making
- Contribute to model development engagement with the lines of business and represent TMA in model development activities with the model stakeholders
- Work with a wide variety of stakeholders from General Technology to Treasury, Finance, and Line of Business leadership
- Development and implementation of Board-level modeling and analytics and execute on model development protocols
Data processing: Collect very complex information and process it ready for decision-making
- Development of very complex methods, processes or analyses as well as improvements
- Propose advances in model design and data analysis.
- Benchmark DB's approach against industry best practices and drive applicable improvements.
Education and Experience:
- Relevant university degree (Master's or PhD) in a quantitative discipline with a programming concentration (e.g., Economics, computer science, applied statistics/mathematics, engineering, Physics, etc.)
- Three to five years of relevant professional experience in a coding and modeling discipline is necessary.
- Very strong quantitative background, extensive analytical skills and ability to efficiently solve problems independently and proactively.
- Extensive recent hands-on modeling experience in the following key modeling topics: linear and/or non-linear generalized linear mixed models, PCS & Factor analysis, state-space models, panel data analysis, and account-level logistics.
- Knowledge of Deposit, Loan, Treasury, ALM, Liquidity, and Interest Rate Risk principles and relevant interdependencies
- Proficiency in R, and other programming capabilities such as Python and Visual Basic