Key Responsibilities
- Perform data cleanup and data quality activities to identify, correct, and resolve inconsistencies, duplicates, missing information, and other data issues.
- Support data migration activities, ensuring accurate and complete transfer of data between systems.
- Develop and maintain data mapping documentation to ensure source data is correctly aligned with target systems and business requirements.
- Conduct data review and analysis to identify trends, anomalies, gaps, and opportunities for improving data quality and usability.
- Work with insurance and broker databases, reviewing and validating data relevant to insurance operations and business processes.
- Support initiatives to build an AI-ready organization by ensuring data is accurate, structured, consistent, and suitable for analytics and future AI applications.
- Collaborate with business and technical stakeholders to understand data requirements, investigate data issues, and support data-related projects.
- Create reports, dashboards, and data visualizations to communicate findings and support business decision-making.
Required Skills & Qualifications
- Experience in data analysis, data quality, data migration, data mapping, or related data-focused roles.
- Strong analytical and problem-solving skills with attention to detail.
- Advanced working knowledge of Microsoft Excel.
- Experience with Python for data analysis, manipulation, and/or data processing.
- Experience with Power BI for reporting, dashboards, and data visualization.
- Ability to work with large datasets and identify data quality issues.
- Strong understanding of data structures, data validation, and data management concepts.
- Good communication skills and ability to work with both business and technical stakeholders.
Preferred Background
- Experience working with insurance or broker databases.
- Background in insurance and/or accounting is preferred.
- Experience supporting data migration and transformation projects.
- Exposure to AI/data readiness initiatives or preparing organizational data for advanced analytics and AI use cases.