Data Analyst

ROLE TITLE Claims Data Analyst UNIT Claims Business Analyst ROLE SUMMARY Seeking a highly skilled and detail-oriented Senior Claims Data Analyst. Candidates considered for this role must have extensive experience with Guidewire ClaimCenter and ETL tools to ensure seamless data mapping, migration, and reporting. The analyst will also provide insights and solutions to enhance data accuracy and operational efficiency. In addition, the analyst will collaborate with cross-functional teams to identify trends, improve processes and deliver innovative solutions that drive efficiency and improve customer outcomes. ROLE 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. TECHNICAL 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. GENERAL QUALIFICATIONS Strong problem-solving and critical-thinking stills, 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 REQUIREMENTS 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.