Overview

Support Internal Audit's evaluation of model risk frameworks and their ability to mitigate risk for individual models and in the aggregate. Conduct reviews of complex data science and machine learning models across the organization through audit engagements and technical reviews of models. Serve as a subject matter expert to Internal Audit staff, senior management and business partners on end-to-end life-cycle management of model development, implementation, ongoing monitoring, regulatory expectations, and industry modeling practices. Conduct work assignments of increasing complexity, under moderate supervision with some latitude for independent judgment. Intermediate professional within field; requires moderate skill set and proficiency in discipline.

• Responsible for assessing model governance processes including model inherent risk ratings, model validations, materiality of model changes, and other reviews of models as part of model -related governance audits
• Leverages specialized technical approaches to develop, implement, and execute model testing plans for models that require expert model risk knowledge and skills
• Executes independent internal audit reviews of models to ensure the independent model audit process compliant with the written risk and compliance policies and procedures at a subject matter expert level
• Evaluates model development, implementation, and use as it pertains to elements of model conceptual soundness, model assumptions, modeling methodology, model limitations, data quality, ongoing monitoring, and other more complex elements of the model development process
• Identifies meaningful insights from large data and metadata sources
• Test hypotheses/models, analyze, and interpret results
• Exercise sound judgment and discretion within defined procedures and practices
• Develop and code moderately complex software programs, algorithms, and automated processes
• Use modeling and trend analysis to analyze data and provide insights
• Develop understanding of best practices and ethical AI
• Transform data into charts, tables, or format that aids effective decision making
• Build working relationships with team members and subject matter experts
• Lead small projects and initiatives
• Utilize effective written and verbal communication to document and present findings of analyses to a diverse audience of stakeholders

• 3-5 years of experience in exploratory data analysis
• Basic understanding of business and operating environment
• Statistics
• Programming, data modeling, simulation, and advanced mathematics
• SQL, R, Python, Hadoop, SAS, SPSS, Scala, AWS
• Model lifecycle execution
• Technical writing
• Data storytelling and technical presentation skills
• Research Skills
• Interpersonal Skills
• Working knowledge of procedures, instructions, and validation techniques
• Model Development
• Communication
• Critical Thinking
• Collaborate and Build Relationships
• Initiative with sound judgement
• Technical (Big Data Analysis, Coding, Project Management, Technical Writing, etc.)
• Sound Judgment
• Problem Solving (Responds as problems and issues are identified)
• Bachelor's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields

• Master's/PhD Degree in Data Science, Statistics, Mathematics, Computers Science, or Engineering
• Prior experience with enterprise risk management or internal audit
• Deep knowledge and experience with SR 11-7 and/or ASOP 56
• Prior experience with credit risk
• Knowledge of one or more regulations such as CECL, CCAR, Anti-Money Laundering, Fair Lending, etc.
• Advanced knowledge of Navy Federal Credit Union instructions, standards, and procedures