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# Insurance Data Specialist - Analytics

- **Company:** Amazon.com, Inc.
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Expert
- **Salary:** $83,200.0 - $98,571.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Spreadsheets, Databases, Data Governance, R (Programming Language), Python (Programming Language), Operational Data Store, Power BI, SQL Databases, Tableau (Software), Data Management, Looker Analytics
- **Published:** September 2, 2026
- **Apply:** https://www.careerjet.com/jobad/us9a7c7fa8d35868bd49ce6df75c588dc4

## About the Role

* 2+ years of professional experience in insurance data, business analysis, reporting, operations analysis, quality assurance, or process improvement.
 * Understand at least one insurance operating domain, such as underwriting, policy administration, claims, distribution, health-plan operations, reinsurance, or compliance.
 * Translated business questions into metrics, reporting requirements, data definitions, workflow changes, or operational controls.
 * Analyze a process without substituting for the underwriter, adjuster, clinician, actuary, or compliance specialist responsible for the substantive decision.
 * Excellent analytical writing, structured problem-solving, and high attention to detail.
 * Proficient with spreadsheets and at least one reporting, database, analytics, or workflow tool.

Preferred

 * Experience with SQL, Python, R, Tableau, Power BI, Looker, or insurance data platforms.
 * Lean, Six Sigma, project-management, business-analysis, or data-governance credential.
 * Experience with policy, billing, claims, CRM, provider, or member-administration systems.
 * Data governance, model governance, audit, or operational quality experience.
 * Experience developing KPIs, service-level metrics, or executive reporting.

## Description

* Design realistic scenarios involving policy, premium, exposure, claim, provider, member, producer, and operational data.
 * Create work products such as metric definitions, data-quality assessments, workflow analyses, dashboard requirements, operational reports, root-cause analyses, and process-improvement recommendations.
 * Write "golden" reference responses at experienced insurance data and operations quality.
 * Grade AI-generated responses against structured rubrics for data interpretation, metric consistency, process understanding, feasibility, and communication.
 * Identify incorrect denominators, misleading aggregations, inconsistent definitions, data-lineage gaps, workflow bottlenecks, and conclusions not supported by the available evidence.
 * Provide written feedback the research team uses to improve model behavior., PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.


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