Audit Data Analytics – Insurance
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Job Description
Audit Data Analytics Manager leading data-driven strategies and solutions for audit processes. Collaborating with teams to enhance audit quality, efficiency, and insights in the insurance sector.
Responsibilities:
- Lead the development and execution of data-driven strategies to enhance audit quality, efficiency, and insights
- Combine technical expertise in data analytics with a deep understanding of audit processes to deliver innovative solutions that support risk assessment, testing, and continuous monitoring
- Analyze large datasets to identify anomalies, trends, and potential control weaknesses
- Design and implement advanced analytics solutions to support project objectives
- Develop dashboards, visualizations, and automated tools for engagement teams
- Collaborate with examiners to integrate analytics into planning, fieldwork, and reporting
- Maintain clear documentation to support methodologies and processes
- Identify opportunities to improve examination coverage and efficiency through data-driven techniques
- Provide consultation and support services on process improvement, data governance, artificial intelligence, and data analysis
- Monitor project budget using client invoices and expense information with the ability to forecast budget shortfalls in advance
- Conduct client status meetings, review deliverables, receive client sign-off, escalate issues and communicate client opportunities
Requirements:
- Bachelor’s degree in Data Analytics, Computer Science, Finance, Risk Management, Accounting, or related field
- 5+ years of insurance industry experience
- Strong understanding of ERP systems and data structures
- Knowledge of emerging technologies such as AI and machine learning in audit contexts
- Experience with IT security in areas such as: Windows, Unix, routers, switches, database environments, web security, firewall and IDS/IPS, RACF, ACF2, z/OS, wireless
- Understanding of basic data warehousing architecture, database concepts such as normalization and denormalization, and the difference between OLTP (On-Line Transaction Processing) and OLAP (On-Line Analytical Processing)
- Proficiency in SQL, Python, or R for data analysis
- Proven experience with audit analytics tools (e.g., ACL, IDEA) and data visualization platforms (e.g., Power BI, Tableau)
- Ability to conduct fact-finding research and utilize problem-solving techniques
- Ability to collect, evaluate, and analyze large data files to identify patterns and develop phases of regulatory recommendations
- Ability to organize data into logical format for presentations in regulatory reports, documents and other written materials
- Ability to present and communicate complex data issues and solutions to both internal and external clients
- Demonstrated problem-solving skills to write code
- Demonstrated history of project management experience
- Strong interpersonal, presentation, analytical and statistical sampling skills
- Skilled in team building and team development.
Benefits:
- Competitive benefits and compensation package
- Flexibility in schedule to balance life's demands
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