About This Role
This role is for a Manager in a Model Validation team within the Model Risk Office, responsible for validating payment network business models. It involves working closely with business groups and requires strong communication skills to engage with diverse stakeholders, regardless of their technical background.
Responsibilities
- Perform independent model validations for payment network models, including fraud, AML, counterparty, and financial models, in accordance with regulatory guidance SR 11-7 and internal model risk policy and standards
- Validate fraud and AML modeling approaches, including rule-based systems and thresholds, statistical models, and machine learning models (e.g., Gradient Boosting, Random Forecast)
- Remain on the leading edge of analytical technology with a passion for the newest and most innovative tools
- Understand relevant business processes and portfolios associated with model use
- Understand technical issues in econometric, statistical, and machine learning modeling and apply these skills toward developing models and assessing model risks and opportunities
- Communicate technical subject matter clearly and concisely to individuals from various backgrounds both verbally and through written communication
- Prepare presentations of complex technical concepts and research results to non-specialist audiences and senior management
- Maintain the efficiency and accuracy of models through continuous improvement and application of best practices
- Develop and maintain high quality and transparent documentation
- Leverage the latest open-source technologies and tools to identify areas of opportunity in the existing framework
Requirements
- Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
- A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics
- A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics
- A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics
- At least 1 year of experience leveraging open source programming languages for large scale data analysis
- At least 1 year of experience working with machine learning
- At least 1 year of experience utilizing relational databases