Insurance Data Specialist - Analytics

• 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.

Must-Have

• 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.

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D’Angelo, Larry Summers, and Jack Dorsey.