Claims AI & Analytics Engineer

AssuranceAmerica

$95K — $115K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor’s degree in Computer Science, Information Systems, Analytics, Engineering, or a related field.
  • 5+ years in analytics engineering, business intelligence, or data-focused technology roles.
  • Strong SQL skills and programming experience, preferably in Python.
  • Proficiency with BI tools like Power BI or Tableau.
  • Experience with cloud-based platforms and integrations.
  • Knowledge of APIs, ETL processes, and data orchestration frameworks.
  • Strong analytical and problem-solving skills.

Responsibilities

  • Design and support scalable claims data pipelines and reporting infrastructure.
  • Develop automation solutions to enhance claims workflow and reporting efficiency.
  • Build and maintain analytical data structures and ETL/ELT processes.
  • Support the modernization of analytics platforms and cloud environments.
  • Collaborate with cross-functional teams to improve data governance and integration.
  • Develop analytics solutions for claims workflow optimization and segmentation.
  • Establish data validation and audit-readiness controls to ensure data integrity.

Benefits

  • Opportunity to work within a collaborative, cross-functional environment.
  • Engagement with cutting-edge technologies including AI and predictive analytics.
  • Potential for impactful contributions aimed at optimizing claims operations.
  • Exposure to cloud-based platforms in a modern tech stack.
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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