Patient Financial Services AI Reviewer

About OpenTrain

OpenTrain is the #1 platform for people building careers in AI training and data labeling. We connect experienced contributors with paid projects where they teach and shape how AI systems behave — helping you track work, grow a portfolio, and build a durable freelance career in a fast-growing industry.

About AI training work in this role

AI training (data labeling and RLHF) is the human side of building trustworthy AI. In this project you'll evaluate AI outputs — reviewing text the model writes and giving structured feedback that improves future performance. Work is remote, flexible, and directly influences how AI tools handle patient financial interactions.

The role

OpenTrain AI is hiring experienced patient financial services leaders to evaluate AI tools that support self-pay revenue recovery and patient financial engagement. You will review AI-generated communication drafts, payment plan recommendations, and resolution strategies for clinical billing contexts, giving structured ratings and written feedback used to train and fine-tune models.

• Position type: Contractor, part-time (20+ hours/week)
• Pay: $92 USD per hour (PAY_PER_HOUR)
• Location: United States only; English required

What you'll do

You will combine domain expertise with careful evaluation skills to judge AI outputs for accuracy, legal compliance, and patient experience. Tasks focus on patient collections, early-out and bad debt workflows, and payment plan administration.

• Review AI-generated patient financial communications and rate them for clarity, accuracy, and compliance
• Assess AI payment plan recommendations and self-pay resolution strategies for appropriateness
• Lead or advise on self-pay collection strategy across pre-service, point-of-service, and post-service touchpoints
• Coordinate with billing, financial counseling, and bad debt recovery teams to improve self-pay capture
• Monitor and report on KPIs such as collection rates, conversion rates, write-off rates, and patient satisfaction
• Provide structured feedback and annotation to create training labels (evaluation ratings, RLHF) for model improvement
• Support compliance with FDCPA, HIPAA, state collections laws, and internal patient financial assistance policies

Requirements

This is an expert-level role that requires real-world leadership in patient financial services and comfort evaluating AI-generated content in a regulated environment. Preserve confidentiality and follow privacy rules when handling sample records used in training.

• 5+ years experience in patient collections, self-pay revenue cycle, or patient financial services
• At least 2 years in a leadership role managing collections or revenue cycle teams
• Deep knowledge of self-pay collection workflows and FDCPA compliance; working knowledge of HIPAA and state collections rules
• Experience with early-out and bad debt collection programs, including vendor oversight
• Proficiency with EHR systems and patient collections/billing platforms
• Exceptional written and verbal English communication skills
• Comfort evaluating AI-generated patient financial content for accuracy and compliance
• CRCR, CHAM, or similar revenue cycle certification preferred

Who should apply

Apply if you are an experienced patient financial services leader who wants part-time, remote work that directly shapes AI used in healthcare billing and collections. This role suits practitioners who care about compliance, patient experience, and measurable revenue outcomes.

• Experienced managers or directors of patient collections, self-pay, or revenue cycle operations
• Revenue cycle professionals with hands-on experience in payment plans, early-out, and bad debt workflows
• People comfortable giving clear, structured feedback and working with model evaluation workflows (RLHF, ratings)

How it works

You will be contracted by OpenTrain AI and complete evaluation tasks through our platform. Work is measured by labels and ratings you submit; examples and instructions will be provided for each batch. Maintain confidentiality; do not submit protected health information except within approved, de-identified training materials.

• Labeling/data type: Text evaluation (EVALUATION_RATING, RLHF)
• Schedule: Flexible — 20+ hours per week expected
• Employment: Contractor, part-time
• Compensation: $92/hour (USD)
• Location: United States only; English required
• Tools: You should be comfortable accessing EHR screenshots or billing examples and using web-based annotation/evaluation interfaces