Senior Data Analyst (Internal Audit Analytics)

The Senior Data Analyst (Internal Audit Analytics) provides risk-focused analytical and statistical insights to Internal Audit leadership and stakeholders. The role delivers modeling and analytics on large data sets, supports audit engagement needs, and helps ensure reporting quality and data integrity.

Key Responsibilities

• Perform complex analytical and statistical modeling on large data sets to provide actionable intelligence on key risks to business processes and controls.
• Define data requirements and execute end-to-end data activities, including collection, processing, cleaning, analysis, modeling, and visualization across systems and data from multiple lines of business.
• Lead complex data analysis projects with minimal supervision, applying independent judgment throughout.
• Advise audit teams and other stakeholders on data analytics best practices for audit engagements.
• Manage projects from inception through deployment and ongoing maintenance.
• Collaborate with technology teams and business end-users to understand data and analysis needs and translate them into technical requirements, including data definitions, business rules, and data quality requirements; conduct data UAT and data accuracy, validation, and integrity research.
• Meet deliverable reporting requirements through quality data audits and analysis.
• Identify and compile datasets using a variety of tools to support predicting, improving, and measuring outcomes for business-to-business objectives.
• Resolve complex data quality issues using advanced data profiling, cleansing, and monitoring approaches to maintain integrity and reliability.
• Develop and implement advanced data cleaning and validation processes, including outlier detection, imputation methods, and anomaly detection.
• Clean and organize raw data and produce descriptive statistics to support business intelligence and data science initiatives.
• Partner with data science teams to maintain statistical models for ongoing and ad hoc review and analysis.
• Build working relationships with team members and subject matter experts, including leading small projects and initiatives.

Required Qualifications

• Experience: 5-7 years of experience in data analysis and reporting.
• Business knowledge: complete knowledge and understanding of the business area or specialization.
• Programming and data prep: data manipulation and scripting skills using SQL, Python, or R, including advanced data cleaning and preprocessing techniques and tools.
• ETL and analytical methods: effective skill with ETL tools and techniques, along with data cleaning and other analytical techniques required for data usage.
• Statistics: advanced knowledge of statistical analysis concepts including measures of central tendency, normal distribution, variance, standard deviation, basic tests, correlation, and regression techniques.
• Modeling interpretation: advanced ability interpreting, extrapolating, and interpolating data for statistical research and modeling.
• Data structures and extraction: knowledge of various data structures and the ability to extract data sources (e.g., PySpark, PowerBI).
• Governance: strong understanding of data governance principles and practices.
• Education: Bachelor’s Degree in Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields.
• Additional education: a Master’s degree in Business, Finance, Statistics, Information Systems, Computer Science, Data Science, Data Analytics, or a related field.
• Risk and audit experience: experience in Compliance, Operational Risk, Enterprise Risk Management, Internal Audit, or similar.
• Cloud: experience with cloud platforms (e.g., Azure).
• Anomaly detection: experience with anomaly detection techniques (e.g., unsupervised learning).
• MS SQL and BI tools: advanced knowledge and experience working with MS SQL, SSIS, SSRS, SSAS.
• Internal policies: working knowledge of Navy Federal Human Resources policies, procedures, and programs.
• Work authorization: Applicants must be authorized to work in the United States without the need for current or future sponsorship.

Location and Schedule

• Onsite location: Vienna, VA
• Office addresses: 820 Follin Lane, Vienna, VA 22180; 5510 Heritage Oaks Drive, Pensacola, FL 32526; 141 Security Drive, Winchester, VA 22602
• Hours: Monday - Friday, 8:00AM - 4:30PM

Compensation

USD 96,900 - 141,600 per year.

Technology and Skills

• SQL, Python, R
• ETL, PySpark, PowerBI
• Azure
• MS SQL, SSIS, SSRS, SSAS
• Outlier detection, imputation methods, anomaly detection, unsupervised learning