Claims Data Analyst

Responsibilities

• Analyze large datasets related to commercial Property & Casualty (P&C) claims to identify trends, anomalies, and opportunities for improvement.
• Develop and maintain dashboards, reports, and visualizations to communicate key metrics and findings to stakeholders.
• Perform root cause analysis for claims performance issues and recommend data-driven solutions.
• Provide insights to enhance claims handling processes, reduce costs, and improve overall operational efficiency.
• Identify opportunities for automation of manual processes and implement advanced analytics tools to streamline workflows.
• Collaborate with IT and data engineering teams to improve data quality, enhance data pipelines, and ensure seamless data integration.
• Act as a moderator for the Guidewire ClaimCenter master mapping, consolidating data flows across integrations.
• Analyze and resolve database issues in Guidewire ClaimCenter to maintain data integrity and optimize system performance.
• Work closely with business analysts, managers, and leadership to understand business challenges and translate them into analytical solutions.
• Present findings, insights, and recommendations in a clear, concise manner to non-technical audiences, including senior leadership.
• Provide mentorship and guidance on data analysis best practices and advanced analytical techniques to team members and stakeholders.

Qualifications:

• A minimum of 5 years of experience in data analysis, with a focus on claims, insurance, or the commercial P&C industry.
• Proficient in Guidewire Studio (v.10), TortoiseSVN, Jira, Toad, and SQL Developer.
• Expertise in ETL tools and database technologies, including SQL, PL-SQL, and T-SQL procedures.
• Advanced Excel skills, including VBA and Power Query, for data analysis and reporting.
• Proficiency in data analysis tools such as SQL, Python, or SAS.
• Experience with data visualization tools like Tableau, Power BI, or QlikView.
• Strong understanding of P&C insurance concepts, including claims reserving, loss ratios, and exposure metrics.
• Experience with advanced analytics techniques, such as predictive modeling, clustering, or natural language processing (NLP).
• Familiarity with machine learning concepts and predictive modeling; hands-on experience with AI tools is a plus.
• Extensive experience with claims data, including data migration, integration, and reconciliation processes.
• Hands-on experience with claims management systems (e.g., Guidewire ClaimCenter) is highly desirable.