Insurance Claims Management AI Expert

Weekday AI

4h•Remote

About The Position

This role is for an Insurance Claims Management AI Expert, focusing on optimizing the end-to-end claims lifecycle using AI and advanced analytics. The position requires a blend of domain expertise in insurance claims and hands-on experience in deploying AI-driven solutions to enhance efficiency, accuracy, and customer experience. The expert will design, implement, and optimize intelligent systems across claims intake, investigation, and adjudication workflows, working closely with cross-functional teams including underwriting, fraud detection, legal, and IT to integrate AI models into operational environments.

Requirements

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

Nice To Haves

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

Responsibilities

Design, implement, and optimize intelligent systems across claims intake, investigation, and adjudication workflows.
Work closely with cross-functional teams including underwriting, fraud detection, legal, and IT to ensure seamless integration of AI models into operational environments.
Develop and refine AI models for automated data extraction, classification, and triaging of claims from multiple sources (documents, images, customer submissions) in claims intake.
Improve turnaround time and minimize manual intervention in claims intake.
Leverage machine learning and predictive analytics to identify anomalies, detect potential fraud, and support decision-making in claims investigation.
Contribute to building intelligent workflows that prioritize high-risk claims and assist adjusters with actionable insights.
Help design AI-assisted decision engines that recommend claim outcomes based on policy coverage, historical data, and risk profiles in adjudication.
Ensure consistency and compliance with regulatory standards in adjudication.
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.
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.