Senior Data Scientist (Internal Audit Product Engineering)
Navy Federal Credit Union · Vienna, VA, United States
About The Role
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!
Provide data-driven insights and technology-enabled capabilities that support Internal Audit's strategic objectives and decision-making. Understand Internal Audit’s business needs and identify opportunities to improve audit coverage, operational efficiency, and risk insights through analytics, automation, and AI. Design, develop, and maintain audit-focused data products, workflow automation, and AI-enabled capabilities that support assurance and advisory activities across the audit lifecycle. Contribute to product strategy, solution delivery, testing, deployment, and continuous improvement initiatives while promoting strong data governance, data quality, and responsible AI practices.
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- Develop, maintain, and enhance data products, data pipelines, analytical models, dashboards, and automation solutions to support Internal Audit analytics and decision-making
- Design, build, and enhance agentic AI and workflow automation solutions using AI technologies to drive efficiencies in audit processes
- Partner with auditors, business stakeholders, and technology teams to understand requirements and translate business challenges into scalable analytical solutions
- Support automated control testing, population-based analytics, continuous monitoring, and audit automation initiatives
- 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, Computer Science, Engineering, or degrees in similar quantitative fields
Desired Qualifications
- Master's/PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or Engineering
- Experience with Alteryx, Databricks, Azure Data Lake, Microsoft Copilot Studio, Power Automate, Power Apps and Azure AI Foundry
- Experience using Python and related data science libraries such as Pandas, NumPy, PySpark, Scikit-learn, or similar frameworks for data analysis, automation, and model development
- Experience building dashboards and reporting solutions using Power BI or similar visualization tools
- Experience managing the end-to-end product and solution lifecycle, including requirements gathering, solution design, testing, user acceptance testing (UAT), deployment, and ongoing support
- Knowledge of data governance, data quality controls, data lineage, and data management best practices
- Experience working within audit, risk management, compliance or financial services
- Experience working in Agile product development environments and collaborating with cross-functional teams
- Demonstrated curiosity, innovation mindset, and ability to identify opportunities to automate manual processes
Additional Information
Hours
- Monday - Friday, 8:00AM - 4:30PM
Location
- 820 Follin Lane, Vienna, VA 22180
- 5510 Heritage Oaks Drive, Pensacola, FL 32526
- 141 Security Drive, Winchester, VA 22602
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