HelloFreshSydney, New South Wales, Australia11h ago
AmazonPosted 3w ago
Revenue Cycle Consultant, Healthcare Finance Operations at Amazon scores 45 out of 100 on AI centrality, which makes it AI Level 2 of 4 (Uses AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
Analyze healthcare revenue cycle defects and operational inefficiencies using data-driven methods and AI-assisted analytics tools.
Through data-driven analysis and manual review, you will identify patterns among aged receivables, analyze billing and cash receipts reports, and surface trends that contribute to revenue leakage, claim denials, and operational inefficiencies. You will leverage your knowledge of AI-assisted analytics and statistical methods to strengthen the rigor of your findings, ensuring that each defect paper provides clear evidence, quantified impact, and actionable root cause analysis.
The ideal candidate brings strong healthcare revenue cycle expertise, demonstrates exceptional analytical capabilities, possesses an eye for detail and process improvement, and has a proven ability to translate complex data into clear, evidence-based documentation. Experience with statistical methods, AI-enabled tools, and a passion for experimentation are highly valued.
The Finance Operations organization works with every part of Amazon to provide procure-to-pay, revenue-to-receipt, real-estate and facilities, operations accounting and operations excellence services with the highest level of controllership at the lowest cost to the company. We provide the backbone systems and operational processes which completely, accurately, and validly pay Amazon's suppliers, invoice our customers and report financial results. Amazon is quickly building the Finance Operations capabilities in the healthcare industry by creating the Healthcare Finance Operations Services.
Key job responsibilities
In this analytical role, you will identify and investigate revenue cycle defects across billing, collections, cash application, and denial management processes. Your primary focus will be discovering issues through data analysis, forming hypotheses about root causes, and running targeted experiments to validate your findings before packaging them into structured documentation for stakeholder action.
- Analyze coding, charge capture, billing, cash receipts, and accounts receivable reports and activities to identify defects, anomalies, and trends that impact revenue, cash flow, and operational efficiency
- Hypothesize about potential defects based on observed patterns, denial trends, and system behaviors, then design and execute experiments (through analytics or manual review) to prove or disprove defect existence and quantify impact
- Package validated defects into structured defect analyses that clearly articulate the problem, evidence, root cause analysis, quantified financial impact, and recommended resolution path for technology and operations stakeholders
- Leverage AI-enabled tools and awareness of emerging AI/ML capabilities to enhance defect detection, automate pattern recognition, and improve the speed and accuracy of analytical workflows
- Apply statistical methods and experimental design principles to ensure rigor in defect validation, including appropriate sampling, significance testing, and data-driven conclusions
- Identify trends and categories among aged receivables, denial patterns, and payer behaviors; provide clear, actionable feedback to stakeholders to improve results and prevent recurrence
- Identify trends and develop insights that ultimately reduce cost and improve revenue lift
- Analyze workflow and operational procedures to identify opportunities for improved reimbursement; document findings and present recommendations to leadership
- Produce clear, well-structured technical writing including defect analyses, root cause analyses, and process documentation that effectively communicates complex findings and processes to both technical and non-technical audiences
- Coordinate cross-functionally to analyze data drivers, develop comprehensive insights, and present clear, actionable findings to key stakeholders including technology teams, operations, and finance
- Contribute to the evaluation of AI initiatives and explore how automation, machine learning, and robotic process automation (RPA) can enhance defect detection and resolution workflows
Basic qualifications
- 3+ years of tax, finance or a related analytical field experience
- 3+ years of healthcare revenue cycle experience within registration, scheduling, billing, cash collection, cash application, or denial management/follow-up
- Medical billing experience with an understanding of healthcare reimbursement processes, third-party payer guidelines, and compliance requirements
- Demonstrated ability to analyze processes and information, identify problems and trends, and develop effective solutions and strategies
- Strong technical writing skills with the ability to clearly document findings, articulate complex issues, and communicate effectively in written form to diverse stakeholders
- Ability to work independently, handle multiple tasks, and exhibit problem-solving skills with an exceptional eye for detail
Preferred qualifications
- 4+ years of healthcare revenue cycle experience in a hospital or physician provider setting
- Coursework or applied experience in statistics, experimental design, or quantitative research methods
- Professional certifications such as CPC (Certified Professional Coder) or CRCR (Certified Revenue Cycle Representative), Certified Coding Associate (CCA), Certified Coding Specialist (CCS)
- Awareness of AI/ML tools and their application to data analysis, pattern recognition, and process automation in revenue cycle contexts
- Experience writing structured analyses, research papers, or technical documentation that translates complex findings for diverse audiences
- Extensive knowledge of critical business processes including Coding, Charge Capture, Billing, Collections, Cash Application, Dispute and Denial Management
- Knowledge of system interfaces with Accounts Receivable and experience identifying incomplete or inaccurate data and determining root causes
- Experience creating process improvements through analysis and automation
- Experience with electronic health record systems and clearinghouse platforms
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, VA, Arlington - 66,900.00 - 117,100.00 USD annually
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Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where data analysis was part of your work. What did you do?
- Tell me about a project where revenue cycle was part of your work. What did you do?
- Tell me about a project where defect analysis was part of your work. What did you do?
- Tell me about a project where statistical methods was part of your work. What did you do?
- Walk me through how you've used AI Enabled Tools in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Data Analysis, Revenue Cycle, Defect Analysis, Statistical Methods, and AI Enabled Tools. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Put the AI tool in a bullet point about what you did, not just in a skills list — this role treats it as a required part of the job.
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