Data Insights Specialist
3 weeks ago
Estimated Salary: $60,000 - $90,000 per year (dependent on experience)
Location: Remote - Atlanta, GA
The role of an Insurance Data Analyst Lead at Georgia IT Inc involves working with large datasets in the property and casualty insurance industry. As a key member of the team, you will be responsible for data extraction, compilation, and analysis to support business decisions.
About the Job:
This is a six-month contract opportunity that requires an experienced professional to work with complex datasets, identifying trends, patterns, and correlations. The successful candidate will have strong analytical skills, knowledge of industry trends, and excellent communication skills to convey findings to non-technical stakeholders.
Key Responsibilities:
- Data Extraction and Compilation: Utilize industry knowledge to identify relevant data sources, extract pertinent information, and compile datasets for analysis.
- Advanced Data Mining: Apply sophisticated techniques to uncover patterns, trends, and correlations within large datasets, contributing to predictive models and risk assessment strategies.
- Stakeholder Collaboration: Work closely with internal stakeholders to define data requirements, ensuring alignment with business objectives and providing guidance on data collection and quality enhancement.
- Data Visualization: Use mapping and visualization tools to transform raw data into easily interpretable visual representations, facilitating insights and decision-making processes.
- Insight Communication: Actively participate in data-related discussions, contributing industry expertise to shape data strategies and solutions addressing business challenges.
- Reporting and Presentation: Prepare and present clear, concise, and actionable reports, dashboards, and presentations to communicate findings, recommendations, and insights to non-technical collaborators.
- Data Integrity Monitoring: Continuously monitor data accuracy, consistency, and completeness, identifying and addressing anomalies or discrepancies to maintain data integrity.
- Process Improvement: Collaborate with data engineers and other technical teams to identify opportunities for process automation, data pipeline improvements, and data quality enhancements.
- Industry Knowledge: Stay up-to-date with industry trends, best practices, and new technologies in data analysis, insurance, and related domains.
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