Model risk is the potential for adverse consequences (e.g., financial loss, poor business or strategic decisions, reputational damage) arising from decisions based on incorrect or misused model outputs and reports. Navy Federal needs to ensure models are tested, challenged on current model usage and practices, and assessed on the effectiveness for their intended uses.
Requirements
- Leverage technologies – including Python and R – to analyze and gain insights within large data sets
- Evaluate model design and performance and perform champion/challenger development.
- Analyze model input data, assumptions, and overall methodology.
- Using statistical practices, analyze current and historical data to make predictions, and identify risks, and opportunities, enabling better decisions on planned/future events
- Provide analytics insights and solutions to solve complex business problems
- Examine data from multiple sources and share insights with leadership and stakeholders
- Conduct a complete independent model validation, which may include, but is not limited to, assessments of the following: Model theoretical framework, fitting methods, assumptions; Data creation process, including data preparation and data quality; Model specification; Model development and performance testing, which may include in-sample, out-of-sample, out-of-time backtesting, sensitivity testing, stress testing, and performance monitoring results; Ongoing monitoring plan, including proposed or existing ongoing monitoring metrics and thresholds; Appropriateness of the implementation testing plan scope in context of associated model risk, testing metrics, and user acceptance testing (UAT); Code and calculations associated with development/estimation and/or implementation; Model documentation including completeness, accuracy, level of details
Responsibilities
- Leverage technologies – including Python and R – to analyze and gain insights within large data sets
- Evaluate model design and performance and perform champion/challenger development.
- Analyze model input data, assumptions, and overall methodology.
- Using statistical practices, analyze current and historical data to make predictions, and identify risks, and opportunities, enabling better decisions on planned/future events
- Provide analytics insights and solutions to solve complex business problems
- Examine data from multiple sources and share insights with leadership and stakeholders
- Conduct a complete independent model validation, which may include, but is not limited to, assessments of the following: Model theoretical framework, fitting methods, assumptions; Data creation process, including data preparation and data quality; Model specification; Model development and performance testing, which may include in-sample, out-of-sample, out-of-time backtesting, sensitivity testing, stress testing, and performance monitoring results; Ongoing monitoring plan, including proposed or existing ongoing monitoring metrics and thresholds; Appropriateness of the implementation testing plan scope in context of associated model risk, testing metrics, and user acceptance testing (UAT); Code and calculations associated with development/estimation and/or implementation; Model documentation including completeness, accuracy, level of details
Other
- The Summer Associate Program is a 12-week internship program beginning in May 2026 and ending in August 2026.
- Students will work on impactful projects and meaningful work during their internship.
- To qualify for this position, applicants must be currently pursuing a degree from an accredited college or university and have an anticipated graduation date of December 2026 or later.
- Review model documentation and meet with business owners as needed to gain an understanding of the model
- Document and quantify the materiality of each finding
- Develop recommendations for model developers to mitigate the risks identified
