Insurance Data Specialist - Analytics - AI Trainer

• 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., Overview: The Senior Specialist, Wholesale Business Analytics supports the merchandising and business management of the JCP Brands and Special Markets portfolio through product a…
• 11 days ago +

• 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.