Responsibilities of this role to include but not limited to:
• Lead and help to drive the consolidation of fraud data and the migration of fraud data warehousing to the Cloud for Security Fraud Division
• Assist in leading efforts to identify data sources and processes in support of highly visible technical initiatives for the Cloud migration
• Provide standard and ad-hoc reporting, including key performance indicator (KPI) reporting, metrics definition and data collection to support KPIs; creation and maintenance of reports and dashboards
• Assist with the organization, collection, processing, and analysis of data to produce and continuously update the use case queues for Fraud Operations; manage the data extraction process for the purpose of data warehousing
• Create database solutions, analyze existing SQL queries for performance improvement, and develop, implement and optimize stored procedures and functions
• Partner with Security Fraud Analytics, IT, and relevant BU SMEs to help teams define and identify data sources, create repeatable data collection processes, and ensure consistent data quality and data ingestion for fraud detection
• Analyze data to discern lessons learned and action items to improve security fraud detection performance and risk posture; partner with teams to help them understand how data can drive improvements and review documentation
• Drive initiatives to fine tune an existing data warehousing to include executing data normalization steps
• Identify and determine acceptable risk tolerance levels to establish information classification standards
• Partner with Fraud Analytics on the design and implementation of data frameworks and pipelines to process data from on-premises and cloud data sources to feed into the data warehouse and data lakes; monitor data quality and implement related controls
• Run and steer the evaluation of existing designs, improve methods, and implement optimizations
• Drive efforts to ensure the security and integrity of solutions including compliance with Navy Federal, industry engineering and Information Security principles and practices
• Assist in leading the analysis and validation of data sharing requirements with internal and external data partners
• Analyze and interpret collected data, identify trends and write reports and recommendations for internal or external clients
• Use statistical practices to analyze current and historical data to make predictions, identify risks, and opportunities enabling better decisions on planned/future events
• Work with business unit leadership to understand data requirements; propose and develop solutions that enable effective decision-making and drive business objectives
• Drive best practices for data analysis, data engineering, and evangelize their usages
• Assist in leading efforts to prepare project deliverables and ensure they are understood by project stakeholders
• Prepare project implementation plans using Agile methodologies, which highlight milestones and deliverables, leveraging standards, practices, and work planning tools
• Recognize potential issues and risks during the analytics project implementation and recommend mitigation strategies

An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against based on disability.  EEO IS THE LAW CC Pace invites any applicant and/or employee to review the Company’s written Affirmative Action Plan.  This plan is available for inspection upon request. If you are an individual with a disability and would like to request a reasonable accommodation as part of the employment selection process, please contact us.