Job Description
We’re initiating a search for a Senior Data Analyst to support a leading insurance provider committed to innovation and excellence.This role is ideal for someone who thrives in a fast-paced, analytical environment and is passionate about using data to drive fraud prevention strategies. playing a key role in developing fraud lead generation scenarios, partnering with cross-functional teams, and delivering insights that shape strategic decisions.________________________________________Key ResponsibilitiesData Exploration & Query Development (80%): Design, code, and test fraud lead generation scenarios using advanced tools like SQL, Snowflake, and SAS.Analytical Frameworks: Define and execute analytical approaches to evaluate potential Billing & Payments fraud leads.Strategic Communication: Collaborate with Fraud Hub leaders, Data Science, and Reporting teams to integrate insights into dashboards and modeling solutions.Operational Storytelling: Lead updates for the Monthly Operational Review (MOR), using data-driven storytelling to highlight performance drivers and actionable recommendations.Coding Standards & Reusability: Establish best-in-class coding practices, document domain-specific expertise, and promote a “build-once-reuse-many” frameworks.________________________________________Skills & QualificationsBachelor’s degree in a quantitative field such as Finance, Economics, Statistics, Mathematics, Computer Science, or a related discipline.Advance English Communication is a must.Experience: 5+ years in data analysis, preferably within insurance or financial services.Technical Proficiency: Strong command of SQL, SAS, , Snowflake, Excel, Power BIIndependence & Initiative: Ability to manage complex analyses with minimal direction;Project Management: Proven ability to meet deadlines, manage stakeholder expectations, and drive engagement.Communication: Excellent collaboration and stakeholder management skills; ability to explain technical concepts to non-technical audiences Preferred Skills (Plus)Financial Acumen: Deep understanding of financial statements, forecasting, and fraud analytics.Experience with Billing & Payments data is a strong plus.Master’s degree is a plus, especially in Data Science, Business Analytics, or Financial Engineering
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