Denials Management & Appeals AI Reviewer

About OpenTrain

OpenTrain is the centralized platform where people start and grow careers training AI. We connect skilled freelancers with hands-on AI training and data-labeling work so you can build a single portfolio of verified projects and apply quickly to roles that match your expertise.

We focus on real, paid work that helps state-of-the-art AI systems learn from expert human judgment — a great opportunity to turn your domain skills into repeatable freelance income while shaping how AI behaves.

Why AI training in healthcare matters

AI training (also called data labeling or human feedback work) is the human side of building AI: experts review model outputs, correct errors, and add structured feedback that becomes training signal. In healthcare revenue cycle work, this means ensuring AI understands payer rules, denial codes, and clinical reasoning so automation helps recover revenue and reduces appeals risk.

This role puts experienced denials managers on the front line of model improvement — your judgments will directly improve appeal quality, denial prevention recommendations, and downstream automation used by revenue cycle teams.

The role

We are hiring a Denials Management & Appeals AI Reviewer to evaluate AI-generated appeal letters, denial root-cause analyses, and denial prevention recommendations. This is hands-on annotation and evaluation work: you will read model outputs, judge correctness and effectiveness, and add structured feedback used for RLHF and evaluation-rating datasets.

This contract, part-time role requires domain expertise in payer rules, CARC/RARC codes, clinical and technical appeals workflows, and revenue cycle KPIs.

• Employment type: Contractor, part-time
• Time requirement: 20+ hours per week
• Location: United States only (remote)
• Language: Fluent English required
• Pay: $70–$93 USD per hour (up to $93/hr)

What you'll do

Your work will be directly tied to improving AI used for denial prevention and appeals. Tasks mix qualitative review, structured annotation, and analytics.

Expect to alternate between single-case reviews and small-scale trend analysis; every review includes adding structured feedback that trains models to produce more accurate, compliant outputs.

• Evaluate AI-generated appeal letters for factual accuracy, clinical rationale, and payer-compliance.
• Review AI denial root-cause analyses and prevention recommendations for correctness and actionability.
• Annotate model outputs with structured feedback for RLHF and evaluation-rating datasets.
• Analyze denial trends by payer, denial code, and denial category to identify systemic root causes.
• Support clinical and technical appeal strategies across commercial, Medicare, and Medicaid payers.
• Check outputs against payer-specific requirements, CMS rules, and timely filing standards.
• Track denial management KPIs such as denial rates, overturn rates, revenue recovery, and days in A/R.

Requirements

You must have hands-on denials management or revenue cycle experience and be comfortable assessing clinical and administrative appeal reasoning. Strong written English and attention to detail are essential because your annotations must be clear and defensible.

• Minimum 5+ years in denials management, appeals, or revenue cycle operations.
• Deep working knowledge of CARC and RARC denial codes and payer denial patterns.
• Experience with clinical and technical appeals including peer-to-peer and external reviews.
• Familiarity with denial analytics platforms, EHR systems, and billing tools.
• Proven ability to judge appeal quality and identify weak or incomplete denial-management reasoning.
• Strong written and verbal English communication skills and precise attention to detail.

Helpful background

The following qualifications are not required but make you especially competitive. List these on your OpenTrain profile to help match you to this work.

• Certifications such as CPC, CCS, CRCR, or CHFP.
• Experience with AI-assisted denial management or revenue-cycle platforms and workflows.
• Background handling medical necessity, experimental/investigational, and level-of-care denials.
• Experience presenting denial performance or recovery metrics to revenue cycle leadership.

How it works and how to apply

This is a remote, contract assignment managed through OpenTrain. You will perform RLHF-style reviews and evaluation-rating tasks: read AI outputs, rate or correct them, and submit structured feedback through the platform. Expect to work independently and follow annotation guidelines that we provide.

To apply, create or update your OpenTrain profile, list your denials and appeals experience, and submit an application. If selected you'll receive instructions, sample tasks, and annotation guidelines before work begins.

• Compensation is hourly: $70–$93 USD per hour; exact rate may depend on experience.
• This role requires US residency and work in fluent English.
• You will be asked to complete sample reviews to validate domain fit before onboarding.