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Open nowPosted 166 days ago

Insurance Claims Management AI Expert

Workable (global search)107,990 open roles

Where
Canada
Work mode
Remote
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Your applicationOpen nowInsurance Claims Management AI ExpertWorkable (global search) · Canada

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7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 6 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
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  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 166 days ago

Workable (global search) median: 6 days open

The posting

This role is for one of our clients

Compensation: $100-$120 per hour (20 hours per week commitment) Job Type: Part-time / Contract

Location: US, UK, Canada, France, Portugal (remote)

We are seeking a highly motivated and detail-oriented Insurance Claims Management AI Expert to join our growing team. This role sits at the intersection of insurance operations, data science, and artificial intelligence, with a strong focus on optimizing the end-to-end claims lifecycle. The ideal candidate will bring a blend of domain expertise in insurance claims and hands-on experience in deploying AI-driven solutions to enhance efficiency, accuracy, and customer experience.

Requirements

Key Responsibilities:

You will play a critical role in transforming traditional claims processes using AI and advanced analytics. Your primary responsibilities will include designing, implementing, and optimizing intelligent systems across claims intake, investigation, and adjudication workflows. You will work closely with cross-functional teams including underwriting, fraud detection, legal, and IT to ensure seamless integration of AI models into operational environments.

In claims intake, you will develop and refine AI models for automated data extraction, classification, and triaging of claims from multiple sources such as documents, images, and customer submissions. Improving turnaround time and minimizing manual intervention will be a key objective.

For claims investigation, you will leverage machine learning and predictive analytics to identify anomalies, detect potential fraud, and support decision-making. You will contribute to building intelligent workflows that prioritize high-risk claims and assist adjusters with actionable insights.

In adjudication, you will help design AI-assisted decision engines that recommend claim outcomes based on policy coverage, historical data, and risk profiles, ensuring consistency and compliance with regulatory standards.

Core Functional Expertise:

  • Reserve Setting and Loss Estimation: Develop predictive models for accurate reserve setting and loss estimation using historical claims data, actuarial inputs, and real-time indicators. Continuously refine models to improve forecasting accuracy and reduce financial leakage.
  • Subrogation and Recovery: Design intelligent systems to identify subrogation opportunities early in the claims lifecycle. Implement AI tools to track recovery potential, automate documentation, and improve recovery rates through data-driven insights.

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Actuarial Science, Insurance, or a related field
  • 2–8 years of experience in insurance claims management, analytics, or AI/ML roles
  • Strong understanding of claims lifecycle processes, including intake, investigation, adjudication, and recovery
  • Hands-on experience with machine learning frameworks (e.g., Python, TensorFlow, PyTorch) and data analysis tools
  • Familiarity with NLP, computer vision, or document processing tools for claims automation
  • Experience working with large datasets and building predictive models

Preferred Skills:

  • Knowledge of insurance regulations and compliance requirements
  • Experience with claims management systems and workflow automation tools
  • Strong problem-solving skills and ability to translate business needs into technical solutions
  • Excellent communication skills to collaborate with both technical and non-technical stakeholders
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