Senior Data Scientist (Internal Audit Model & AI Risk)

Navy Federal•Pensacola, FL

4d•Onsite

About The Position

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 and artificial intelligence (AI) risk and governance frameworks and their ability to mitigate risk at the individual implementation and aggregate levels. 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. Provide independent assurance through assessments of complex data science, machine learning, generative AI, and agentic AI capabilities across the organization through audit engagements and other technical reviews. Evaluate relevant ecosystems by assessing governance frameworks, risk management practices, AI/model lifecycle controls, the effectiveness of oversight activities across the first and second lines of defense, and the complexity, uncertainty, transparency, and operational risks associated with advanced analytical and AI-enabled solutions. Serve as a subject matter expert to Internal Audit staff, senior management, and business partners on end-to-end lifecycle management of AI/model development, implementation, ongoing monitoring, regulatory expectations, and industry practices. Conduct and manage 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. This position is eligible for the TalentQuest employee referral program. If an employee referred you for this job, please apply using the system-generated link that was sent to you.

Requirements

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
Knowledge of AI platforms and ecosystems supporting machine learning, generative AI, and LLM-enabled systems, including Microsoft Copilot Studio, Azure AI Foundry, AWS, and 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
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

Nice To Haves

Prior experience with model validation/ model risk management, AI and Agentic risk management, enterprise 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 and frameworks such as CECL, CCAR, Anti-Money Laundering, ECOA, FCRA, NIST AI Risk Management Framework, ISO/IEC 42001Artificial Intelligence Management System, etc.
Advanced knowledge of Navy Federal Credit Union instructions, standards, and procedures
Master's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or another quantitative or related field

Responsibilities

Responsible for assessing AI and model governance processes including model inherent risk ratings, model validations, materiality of model changes, ongoing performance monitoring, and other targeted model review approaches as part of model related governance audits.
Ability to execute and manage independent internal audit reviews of AI products, AI-enabled systems, and models by leveraging subject matter expertise in AI technologies, model risk, and governance practices.
Follow established audit frameworks and assurance processes to deliver high-quality reviews while effectively managing scope, timelines, stakeholder expectations, and communication throughout the engagement lifecycle.
Leverages specialized technical approaches to develop, implement, and execute model testing plans for models that require expert model risk knowledge and skills.
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