Manager II, Data Science (Audit Product Engineering)

Navy Federal Credit Union•Vienna, VA

6h•$131,700 - $206,450

About The Position

Navy Federal's Internal Audit team is undergoing a significant transformation to become a top-tier Audit function. The vision is to be a trusted advisor to the business by consistently delivering high-quality, risk-focused audit and advisory work. The team is focused on implementing efficient processes, maximizing technology utilization, integrating data analytics into all operations, and investing in its people. This role is part of that exciting journey. The Internal Audit's Manager II, Data Science (Product Engineering) is responsible for leading a team of data analytics, data management, and AI specialists. This team will focus on developing and maintaining data products to enhance the efficiency and effectiveness of Internal Audit. Key responsibilities include establishing continuous monitoring and auditing capabilities to dynamically guide audit coverage across the organization, implementing DevOps best practices throughout the product development lifecycle (from intake to release management), and aligning product development with organizational priorities. The role also involves serving as a subject matter expert for the application of predictive models, AI, and Agentic AI to reduce manual effort and increase insights across the entire audit lifecycle.

Requirements

Must be authorized to work in the United States without the need for current or future sponsorship.

Responsibilities

Leading a team of data analytics, data management, and AI specialists focused on developing and maintaining data products.
Establishing continuous monitoring and continuous auditing capabilities to dynamically guide audit coverage across the organization.
Implementing development operations best practices, from intake and requirements gathering through user acceptance testing and release management.
Aligning product development with Internal Audit and Navy Federal’s organizational priorities.
Serving as a subject matter expert for the use of predictive models, AI, and Agentic AI to reduce manual effort and increase insights throughout the audit lifecycle.