AI and Data Validation

Role Purpose

The AI & Data Validation Specialist is responsible for preparing, validating, and analyzing customer data used during implementation, testing, and onboarding of IAN products.

The role ensures data quality, extraction accuracy, migration integrity, and AI output validation by working closely with Business Analysts, Implementation Architects, Configurators, and QA teams throughout the implementation lifecycle.

Key Responsibilities

• Prepare, cleanse, and validate datasets required for customer implementation.
• Define and maintain test datasets, ground truth data, and validation benchmarks.
• Validate extraction outputs, redaction results, policy comparisons, and data quality assessments.
• Support customer data onboarding, data mapping, and migration validation activities.
• Perform data profiling, reconciliation, and quality analysis.
• Collaborate with Configurators to validate extraction rules, business rules, and decision logic.
• Work with QA teams to develop data-driven test scenarios and validation approaches.
• Analyze AI model outputs and identify data quality or configuration issues.
• Create validation reports, accuracy metrics, and implementation quality dashboards.
• Contribute to best practices for data quality, validation, and AI implementation governance.

Required Skills & Experience

• Bachelor's degree in computer science, Data Science, Information Systems, Engineering, Mathematics, Statistics, or related field.
• 810 years of experience in data analysis, data validation, quality assurance, AI operations, or implementation projects.
• Strong experience in the Property & Casualty (P&C) Insurance domain
• Experience with Intelligent Document Processing (IDP), OCR, data extraction, document classification, or AI-enabled automation solutions.
• Strong understanding of data quality, data profiling, validation, and reconciliation techniques.
• Experience working with structured and unstructured data.
• Experience preparing test datasets, validation datasets, and business data models.
• Understanding of extraction accuracy metrics, false positives, false negatives, and validation methodologies.
• Proficiency in SQL and data analysis tools.
• Strong analytical and problem-solving skills.
• Ability to interpret business requirements and translate them into data validation approaches.
• Proven experience working with insurance carriers and clients across North America or Europe.

Desired Skills

• Exposure to machine learning model validation and monitoring techniques.
• Experience with data migration and customer onboarding projects.
• Familiarity with JSON, APIs, and workflow-driven platforms.
• Experience in Insurance, Financial Services, or other regulated industries.
• Agile/Scrum delivery experience.