Guidewire Data Analyst

Job description: Job Title: Senior Data Analyst – P&C Insurance Location: Hybrid role in Warren, NJ Employment Type: Long Term Contract Kindly Share your resumes to dkannoji@wscs.ai Job Summary: We are seeking a highly skilled Senior Data Analyst with strong Property & Casualty (P&C) Insurance domain experience to support data-driven decision-making across underwriting, claims, pricing, and actuarial functions. The ideal candidate will translate complex insurance data into actionable insights, develop advanced analytics, and partner with business stakeholders to improve profitability, risk management, and operational efficiency. Key Responsibilities: • Analyze large, complex datasets related to P&C insurance including underwriting, claims, policy, loss, exposure, and premium data. Develop and maintain dashboards, reports, and KPIs for business, actuarial, and leadership teams • Perform trend analysis, loss ratio analysis, claims severity/frequency analysis, and profitability studies. Support pricing, reserving, and risk modeling initiatives with high-quality analytical insights. Collaborate with underwriting, claims, actuarial, finance, and IT teams to define data requirements. Ensure data quality, integrity, and consistency across multiple insurance systems. Automate recurring reports and improve analytical processes using advanced tools and scripting • Present insights and recommendations clearly to technical and non-technical stakeholders. Mentor junior analysts and contribute to best practices in analytics and data governance Required Qualifications • Bachelor’s degree in Data Analytics, Statistics, Mathematics, Computer Science, Finance, or related field. 7+ years of experience as a Data Analyst, with strong P&C Insurance domain expertise. Hands-on experience with underwriting, claims, policy administration, and loss data • Advanced SQL skills for data extraction and transformation. Strong experience with BI tools such as Tableau, Power BI, or Qlik. Proficiency in Excel (advanced formulas, pivot tables, macros preferred). Solid understanding of insurance KPIs, loss ratios, combined ratios, and reserving concepts. Strong analytical, problem-solving, and communication skills Preferred Qualifications • Experience with Python or R for data analysis and automation. Exposure to actuarial models, pricing analytics, or predictive modeling. Experience working with cloud data platforms (AWS, Azure, Snowflake, or Databricks) • Prior experience in a carrier, MGA, or insurance consulting environment • Insurance certifications (AINS, CPCU) are a plus