Senior Commercial Insurance Claims Data Specialist

Key Performance Indicators: A highly skilled Claims Data Analyst is required to deliver business insights that drive commercial Property & Casualty (P&C) claims efficiency and effectiveness.

Job Responsibilities:

• Deliver actionable data analysis and reporting on large datasets related to P&C claims, identifying trends, anomalies, and opportunities for improvement.
• Develop and maintain advanced dashboards, reports, and visualizations to communicate key metrics and findings to stakeholders.
• Perform in-depth root cause analysis for claims performance issues and recommend data-driven solutions.
• Provide strategic 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 subject matter expert for the Guidewire ClaimCenter master mapping, consolidating data flows across integrations.
• Analyze and resolve complex 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.

Technical Requirements:

• 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.

General Requirements:

• Strong problem-solving and critical-thinking skills, with the ability to address complex data challenges.
• Proven aptitude for identifying and resolving data quality issues and inconsistencies.
• Excellent communication skills, with the ability to translate complex data into actionable insights for both technical and non-technical audiences.
• Demonstrated ability to work independently and manage multiple priorities in a fast-paced environment.
• Clear and concise verbal and written communication skills.
• Comfortable working in ambiguous situations and capable of overcoming challenges to achieve objectives accurately.
• Effective team player who collaborates well with both technical and business stakeholders.
• Self-motivated and able to see tasks through to completion with minimal guidance.
• Strong time-management skills and the ability to meet individual and team deadlines.
• High attention to detail with a strong focus on data accuracy and integrity.
• Adaptable to evolving business needs and advancements in technology.

Education Prerequisites:

• Bachelor's degree in Data Science, Statistics, Actuarial Science, Mathematics, Computer Science, or a related field.
• Certifications in data analytics or business intelligence (e.g., Certified Analytics Professional, Microsoft Certified : Data Analyst Associate, SAS Certified Data Scientist) are preferred but not required.