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Sr Generative AI Scientist II - (Model Risk)

Cotiviti•United States•🌍 Remote
Full-time3-7
$153k - $180k
per year
👁️ 0 views•📝 0 applications•Posted 9/19/2026•Expires 11/18/2026
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Job Description

Overview Join a recently formed team focused on Model Risk and Responsible AI. The Senior GenAI Scientist II – Risk will apply knowledge and experience to real world problems and seek to utilize their skills to reduce the cost of healthcare and improve health quality and outcomes.

As a Data Scientist on this team, you will focus on three main project areas: Model Validation, Model Metrics and Monitoring, and Responsible AI.

This requires someone with depth in AI/ML/GenAI from a data science perspective, versatility to think in terms of technology systems, and some understanding of emerging areas of Responsible AI and AI Ethics.

This is for an ambitious technologist, with the flexibility and personal drive to succeed in a dynamic environment where they are judged based on their direct impact to business outcomes.

Responsibilities

As a Senior GenAI Scientist II within Cotiviti you will be responsible for delivering solutions that help our clients identify payment integrity issues, reduce the cost of healthcare processes, or improve the quality of healthcare outcomes.

You will work as part of a team and will be individually responsible for the delivery of value associated with your projects. Conduct independent model validation of existing models for benchmarking, assessment, and gauging effectiveness.

Determine aspects of model drift and related data drift for the purpose of model risk management (MRM) to both reduce risk and also find opportunities to drive new revenue growth and innovation.

Apply deep expertise with AI/ML/GenAI model development, including hands-on experience with model building and model evaluation. Benchmark and potentially rebuild existing models as needed using updated data, and potentially newer, more modern and effective algorithms.

Actively drive improvements in model monitoring activities, including methods for model registration, model metadata management, and conceptualizing approaches for related tools and techniques. Complete all respons

Required Skills

AIMLGenAImodel validationmodel metricsmodel monitoringResponsible AIAI Ethicsmodel driftdata driftmodel risk managementmodel buildingmodel evaluationmodel registrationmodel metadata managementhealthcarepayment integritydata sciencebenchmarkingalgorithm developmentinnovation

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