AI Data Quality Analyst (Human-in-the-Loop) (Insurtech)

TL;DR

AI Data Quality Analyst (Insurtech): Reviewing and correcting AI-extracted data from complex insurance documents to ensure high data quality for underwriting workflows with an accent on pattern recognition and root cause analysis. Focus on translating extraction errors into technical requirements and bug reports to improve AI model performance.

Location: Remote (LATAM). Must be able to work in Eastern European time zones with overlap for US stakeholders.

Company

A growth-focused team specializing in data, analytics, and AI solutions to help clients build and scale impactful business systems.

What you will do

• Review AI-extracted data from insurance submissions (SOVs, loss runs) for accuracy, completeness, and consistency.
• Compare extracted fields against source documents and correct data directly in templates or systems.
• Log defects, edge cases, and bugs in Jira with clear reproduction steps and impact analysis.
• Identify recurring patterns in extraction errors and translate them into well-structured user stories and requirements.
• Collaborate with architects and data engineers to refine extraction rules and workflows.
• Utilize LLMs and AI assistants for verification and summarization while maintaining strict quality control.

Requirements

• 3+ years of experience in a data-intensive role such as Data, Business, or QA Analyst.
• Proven ability to perform systematic, repetitive data review with high attention to detail.
• Experience writing structured technical tickets and requirements for engineering teams.
• Advanced Excel skills, including pivot tables, lookups, and data cleansing.
• Strong written English for documentation and communication with distributed teams.
• Ability to work in Eastern European time zones.

Nice to have

• Experience in commercial property insurance or financial services operations.
• Familiarity with Statements of Values (SOVs) or loss runs.
• Exposure to LLMs, RAG, or document intelligence systems as a user or tester.
• Basic SQL knowledge for data validation.
• Previous experience in Human-in-the-Loop (HIL) or AI data quality roles.

Culture & Benefits

• Work with a team of outdoor enthusiasts and growth hackers.
• Opportunity to operate at the cutting edge of AI and data analytics.
• Equal Opportunity Employer commitment regardless of background.
• Focus on solving high-complexity problems with meaningful business impact.