Senior Data Scientist (Model Audit)

Overview

Navy Federal Credit Union currently does not provide sponsorship for this role. Applicants must be authorized to work in the United States without the need for current or future sponsorship.

Navy Federal's Internal Audit team is in the midst of an exciting transformational journey to become a best in-class Audit function! It is our vision to be a preferred advisor to the business by building and cultivating trust through the consistent execution of high-quality and risk-focused audit and advisory work. We're focused on implementing efficient processes, maximizing our use of technology, integrating data analytics into everything we do, and investing in our biggest asset, our people. If this sounds like the type of team you'd like to be a part of, then we want to learn more about you!

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

• 5-7 years of experience in data analysis, statistical modeling or regression analysis, including language models, LLMs and/or Generative AI technologies
• Basic understanding of business and operating environment
• Statistics
• Programming, data modeling, simulation, and advanced mathematics
• SQL, R, Python, Hadoop, SAS, SPSS, Scala, AWS, Databricks
• Model lifecycle execution including model development, validation, and governance
• 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)
• Master's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or another quantitative or related field

• Prior experience with enterprise risk management, model risk management, or internal audit
• Deep knowledge and experience with SR 11-7 and/or ASOP 56
• Understanding of various models and modeling practices used in credit risk management, fraud detection, BSA/AML, operations, treasury & finance, marketing models, etc.
• Knowledge of one or more regulations such as CECL, CCAR, Anti-Money Laundering, ECOA, FCRA, etc.
• Advanced knowledge of Navy Federal Credit Union instructions, standards, and procedures