Claims AI & Analytics Engineer

AssuranceAmerica

$100K — $120K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor’s in Computer Science, Information Systems, Analytics, or related field
  • 5+ years in analytics engineering or data-focused roles
  • Strong SQL and programming skills (Python preferred)
  • Familiarity with BI tools like Power BI or Tableau
  • Experience with cloud platforms and integrations
  • Knowledge of APIs, ETL, and automation frameworks
  • Strong analytical and problem-solving skills

Responsibilities

  • Design and support scalable claims data pipelines and reporting infrastructure.
  • Develop automation solutions that enhance claims workflows and reporting accuracy.
  • Build and maintain claims data models and analytical structures.
  • Modernize claims analytics platforms and cloud environments.
  • Collaborate with cross-functional teams to improve data governance and accessibility.
  • Create analytics solutions for claims segmentation and workflow optimization.
  • Establish data integrity and audit-readiness controls.

Benefits

  • Collaborative work environment with multi-department partnerships.
  • Opportunity to work on cutting-edge AI and analytics technologies.
  • Focus on modernization and improvement of operational processes.
  • Inclusive culture that values innovation and analytical solutions.
  • Potential for professional growth and development in analytics engineering.
Full Job Description

Job Summary:

 

The Claims AI & Analytics Engineer is responsible for designing, developing, and supporting the data, automation, and technology solutions that enable Claims analytics, reporting infrastructure, workflow optimization, and AI-driven insights. This role partners closely with Claims leadership, IT, SIU, Finance, and Data teams to modernize claims data processes, improve operational visibility, and enhance analytics delivery through automation and scalable technology solutions.

The role combines hands-on technical expertise with cross-functional collaboration to support claims operations, reporting infrastructure, predictive analytics initiatives, and enterprise data governance.

 

Responsibilities:

 

  • Design and support scalable claims data pipelines, integrations, and reporting infrastructure.
  • Develop automation solutions that improve claims workflows, operational efficiency, and reporting accuracy.
  • Build and maintain claims-focused data models, ETL/ELT processes, and analytical data structures.
  • Support modernization of claims analytics platforms, cloud-based environments, and BI architecture.
  • Partner with Claims, IT, Finance, SIU, and Data teams to improve data accessibility, governance, and integration.
  • Develop and support analytics solutions for claims segmentation, triage, assignment logic, and workflow optimization.
  • Establish data validation, governance, and audit-readiness controls to ensure data integrity.
  • Support implementation of AI-enabled solutions, predictive analytics, and operational scoring initiatives.
  • Identify opportunities to reduce manual processes through scripting, APIs, orchestration, and automation frameworks.
  • Support analytics platform administration, system integrations, and reporting infrastructure enhancements.
  • Participate in testing, validation, and deployment of analytics-related system and automation enhancements.
  • Maintain technical documentation for data flows, transformation logic, integrations, and reporting frameworks.

 

Qualifications:

 

Required:

  • Bachelor’s degree in Computer Science, Information Systems, Analytics, Engineering, or related field
  • 5+ years of experience in analytics engineering, business intelligence, systems integration, or data-focused technology roles
  • Strong SQL and scripting/programming experience (Python preferred)
  • Experience with BI and visualization platforms such as Power BI or Tableau
  • Experience supporting cloud-based platforms and integrations
  • Understanding of APIs, ETL processes, automation frameworks, and data orchestration
  • Strong analytical, troubleshooting, and problem-solving skills
  • Ability to manage multiple priorities and work cross-functionally

 

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