Navy Federal Credit Union
Summer Associate Internship (Data Scientist - Model Risk Management)
Navy Federal Credit Union, Vienna, Virginia, United States, 22184
Overview
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. Model risk comes down to making informed business decisions by understanding a model's weaknesses or limitations. With a variety of models designed to maintain Navy Federal’s financial stability and its ability to make impactful member-related decisions, it is more important than ever to ensure those models are tested, challenged on current model usage and practices, and assessed on the effectiveness for their intended uses.
The Model Risk Management (MRM) team serves as a 2nd line of defense, and our mission is to:
Be a trusted partner in modeling and risk management
Challenge models and deliver transparency for a common interest across the organization
Deliver model risk as a competitive advantage that benefits our members
Manage model risk, not eliminate it
Collectively become a modeling “Center of Excellence” for the enterprise
MRM is responsible for maintaining a governance framework that standardizes model risk activities from model development through retirement. MRM uses control processes to ensure sound model risk management across all model lifecycle activities.
Core components of Model Risk Management’s role include:
Identification
Maintaining a full inventory of models including documentation, code, and datasets
Assessment
Assessing the conceptual soundness of models and their risk through analysis
Recommending model performance enhancements and risk mitigations
Monitoring
Monitoring model usage, changes, performance, data drift, and production errors
Reporting
Providing an enterprise-level assessment of model risk
Tracking the status of individual model risk findings and approving mitigation/remediation plans
Project – Model Validation:
The Summer Associate will complete an end-to-end validation of one of Navy Federal’s predictive models. This validation would include analyzing the model’s data, conceptual soundness, key assumptions, limitations, estimation, calibration, and implementation as appropriate. The validation may also include developing a challenger model against the original model design. At the conclusion of the validation, the Summer Associate will have identified a list of model risk findings that will be presented to the Model Owner for remediation. The selected model for this project may be within a variety of possible subject domains, such as fraud detection, targeted marketing, underwriting, financial forecasting, and more.
Project Steps:
Review model documentation and meet with business owners as needed to gain an understanding of the model
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
Document and quantify the materiality of each finding
Develop recommendations for model developers to mitigate the risks identified
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.
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
Transform data presented in models, charts, and tables into a format that is useful to the business and aids in effective decision-making
Develop and maintain an understanding of relevant industry standards, best practices, business processes, and technology used in modeling and within the financial services industry
Assess the model’s overall fit/suitability with its intended use and purpose
Provide subject matter expertise to identify models’ key assumptions, limitations, and weaknesses, and recommend practical solutions to mitigate model risk
Prepare and present clear, thorough reports to model developers and model owners explaining the analysis performed, the results of the analysis, and recommendations for improvement
Qualifications
Pursuing master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering or other related field
Ability to understand complex business problems
Skill in communicating actionable insights using data to technical and non-technical audiences
Skill in descriptive, predictive, and prescriptive analytics and modeling
Experience in using classification models to solve business problems
Demonstrates an understanding of the modeling lifecycle
Skill in data mining, data wrangling, and data transformation
Skill interpreting, extrapolating, and interpolating data for statistical research and modeling
Skill in Python or R
Skill in SQL and querying (able to pull/transform your own data)
Location: Remote | 820 Follin Lane, Vienna, VA 22180
About Us
Navy Federal provides much more than a job. We provide a meaningful career experience, including a culture that is energized, engaged and committed; and fierce appreciation for our teams, who are rewarded with highly competitive pay and generous benefits and perks.
Our approach to careers is simple yet powerful: Make our mission your passion.
• Best Companies for Latinos to Work for 2024
• Computerworld® Best Places to Work in IT
• Forbes® 2025 America's Best Large Employers
• Forbes® 2024 America's Best Employers for New Grads
• Forbes® 2024 America's Best Employers for Tech Workers
• Fortune Best Workplaces for Millennials™ 2024
• Fortune Best Workplaces for Women ™ 2024
• Fortune 100 Best Companies to Work For® 2025
• Military Times 2024 Best for Vets Employers
• Newsweek Most Loved Workplaces
• 2024 PEOPLE® Companies That Care
• Ripplematch Recruiting Choice Award
• Yello and WayUp Top 100 Internship Programs
From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of, Navy Federal Credit Union.
Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected Veteran.
Disclaimers: Navy Federal reserves the right to fill this role at a higher/lower grade level based on business need. An assessment may be required to compete for this position. Job postings are subject to close early or extend out longer than the anticipated closing date at the hiring team’s discretion based on qualified applicant volume. Navy Federal Credit Union assesses market data to establish salary ranges that enable us to remain competitive. You are paid within the salary range, based on your experience, location and market position
Bank Secrecy Act: Remains cognizant of and adheres to Navy Federal policies and procedures, and regulations pertaining to the Bank Secrecy Act.
REQNUMBER: 26902
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. Model risk comes down to making informed business decisions by understanding a model's weaknesses or limitations. With a variety of models designed to maintain Navy Federal’s financial stability and its ability to make impactful member-related decisions, it is more important than ever to ensure those models are tested, challenged on current model usage and practices, and assessed on the effectiveness for their intended uses.
The Model Risk Management (MRM) team serves as a 2nd line of defense, and our mission is to:
Be a trusted partner in modeling and risk management
Challenge models and deliver transparency for a common interest across the organization
Deliver model risk as a competitive advantage that benefits our members
Manage model risk, not eliminate it
Collectively become a modeling “Center of Excellence” for the enterprise
MRM is responsible for maintaining a governance framework that standardizes model risk activities from model development through retirement. MRM uses control processes to ensure sound model risk management across all model lifecycle activities.
Core components of Model Risk Management’s role include:
Identification
Maintaining a full inventory of models including documentation, code, and datasets
Assessment
Assessing the conceptual soundness of models and their risk through analysis
Recommending model performance enhancements and risk mitigations
Monitoring
Monitoring model usage, changes, performance, data drift, and production errors
Reporting
Providing an enterprise-level assessment of model risk
Tracking the status of individual model risk findings and approving mitigation/remediation plans
Project – Model Validation:
The Summer Associate will complete an end-to-end validation of one of Navy Federal’s predictive models. This validation would include analyzing the model’s data, conceptual soundness, key assumptions, limitations, estimation, calibration, and implementation as appropriate. The validation may also include developing a challenger model against the original model design. At the conclusion of the validation, the Summer Associate will have identified a list of model risk findings that will be presented to the Model Owner for remediation. The selected model for this project may be within a variety of possible subject domains, such as fraud detection, targeted marketing, underwriting, financial forecasting, and more.
Project Steps:
Review model documentation and meet with business owners as needed to gain an understanding of the model
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
Document and quantify the materiality of each finding
Develop recommendations for model developers to mitigate the risks identified
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.
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
Transform data presented in models, charts, and tables into a format that is useful to the business and aids in effective decision-making
Develop and maintain an understanding of relevant industry standards, best practices, business processes, and technology used in modeling and within the financial services industry
Assess the model’s overall fit/suitability with its intended use and purpose
Provide subject matter expertise to identify models’ key assumptions, limitations, and weaknesses, and recommend practical solutions to mitigate model risk
Prepare and present clear, thorough reports to model developers and model owners explaining the analysis performed, the results of the analysis, and recommendations for improvement
Qualifications
Pursuing master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering or other related field
Ability to understand complex business problems
Skill in communicating actionable insights using data to technical and non-technical audiences
Skill in descriptive, predictive, and prescriptive analytics and modeling
Experience in using classification models to solve business problems
Demonstrates an understanding of the modeling lifecycle
Skill in data mining, data wrangling, and data transformation
Skill interpreting, extrapolating, and interpolating data for statistical research and modeling
Skill in Python or R
Skill in SQL and querying (able to pull/transform your own data)
Location: Remote | 820 Follin Lane, Vienna, VA 22180
About Us
Navy Federal provides much more than a job. We provide a meaningful career experience, including a culture that is energized, engaged and committed; and fierce appreciation for our teams, who are rewarded with highly competitive pay and generous benefits and perks.
Our approach to careers is simple yet powerful: Make our mission your passion.
• Best Companies for Latinos to Work for 2024
• Computerworld® Best Places to Work in IT
• Forbes® 2025 America's Best Large Employers
• Forbes® 2024 America's Best Employers for New Grads
• Forbes® 2024 America's Best Employers for Tech Workers
• Fortune Best Workplaces for Millennials™ 2024
• Fortune Best Workplaces for Women ™ 2024
• Fortune 100 Best Companies to Work For® 2025
• Military Times 2024 Best for Vets Employers
• Newsweek Most Loved Workplaces
• 2024 PEOPLE® Companies That Care
• Ripplematch Recruiting Choice Award
• Yello and WayUp Top 100 Internship Programs
From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of, Navy Federal Credit Union.
Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected Veteran.
Disclaimers: Navy Federal reserves the right to fill this role at a higher/lower grade level based on business need. An assessment may be required to compete for this position. Job postings are subject to close early or extend out longer than the anticipated closing date at the hiring team’s discretion based on qualified applicant volume. Navy Federal Credit Union assesses market data to establish salary ranges that enable us to remain competitive. You are paid within the salary range, based on your experience, location and market position
Bank Secrecy Act: Remains cognizant of and adheres to Navy Federal policies and procedures, and regulations pertaining to the Bank Secrecy Act.
REQNUMBER: 26902