Revenue-cycle analytics / decision-support / RCM reporting leader

$100/hrrate as listed

Evaluate AI-generated revenue cycle analytics — KPI dashboards, denial trend analyses, net revenue models — for accuracy, completeness, and whether the recommendations would survive a CFO review. Mercor is staffing this for an AI research lab; observed pay is around $100/hr on flexible, asynchronous hours.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

What the work involves

You'll review outputs an AI system produces when asked to do the analytics work you already do: build a denials scorecard, explain a swing in days in A/R, model net revenue realization under a payer mix shift, or recommend where to focus a cash acceleration effort. Tasks typically arrive as a prompt plus one or more candidate responses. You judge whether the metric definitions are right, whether the math holds, whether the data assumptions are stated, and whether the conclusion actually follows from the numbers — then write a structured rationale explaining your call.

The hard part is rarely spotting arithmetic errors. It's catching an AI that computes clean AR aging but silently mixes professional and facility populations, cites an HFMA MAP key with a subtly wrong denominator, treats a credit balance as collectible, or produces a confident root-cause narrative from a variance that's really a data quality artifact. Comparison and ranking tasks are common, as is rewriting a flawed output into a reference answer that shows the model what good looks like.

What the screen measures

Verifiable specifics. Which reporting environment, what volume, which KPI set, what you personally owned versus what your team delivered.
Depth under follow-up. Expect to define metrics precisely, name the denominator, and explain where the definition breaks down.
Evaluation judgment. Whether you can separate "wrong" from "unsupported" from "technically correct but useless to an operator," and write that distinction down clearly.
Written English. Rationales are the deliverable; terse or vague feedback fails calibration.

Logistics

Fully remote and asynchronous. Contributors commonly pick up 10–20 hours per week, though volume fluctuates with project batches and there is no guaranteed minimum. Expect an unpaid calibration exercise before paid work begins. The $100/hr figure reflects observed rates for this listing and is not a guarantee — Mercor sets rates per project and per contributor.

What they look for

5+ years in revenue cycle analytics, RCM reporting, or healthcare financial decision-support, including 2+ years leading a team
Deep command of RCM KPIs across patient access, coding, billing, denials, A/R, and collections
SQL-based analysis and BI development in Tableau, Power BI, or equivalent
Financial modeling: net revenue realization, forecasting, budget and variance analysis
Clear, structured written English for evaluation rationales
HFMA CRCR/CHFP or healthcare analytics certification (preferred)

Before you apply

Would you pass this screen?

Drawn from what this listing actually requires. Answered in your browser — nothing is sent to us, and we do not store your answers.

Do you have at least 5 years of experience in revenue cycle analytics, RCM reporting, or healthcare financial decision-support roles?
Years of RCM analytics or reporting experience · required
Have you held a leadership role (manager, director, or above) in revenue cycle analytics, RCM reporting, or RCM operations for at least 2 years?
Leadership experience in RCM analytics · required
Are you proficient with at least one BI tool (Tableau, Power BI, or equivalent) or SQL-based data analysis for healthcare analytics?
BI tool or SQL proficiency · required
Have you worked directly with EHR-integrated analytics platforms or RCM-specific reporting systems in a healthcare setting?
EHR-integrated analytics platform experience · preferred
Do you hold or have you earned a healthcare analytics credential such as HFMA CRCR, CHFP, or equivalent?
Healthcare analytics certification (preferred) · preferred

0 of 5 answered

Included with this listing

Interview prep — 11 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: Can they decompose RCM variance into actionable root causes (not just report a number), and do they have evidence of impact on real operations—denials reduction, AR days, coding accuracy, or collection rate improvement?
A strong answer: Describe a specific scenario (e.g., rising aged A/R, coding denials in one service line, patient access bottleneck) with the analytical steps you took (segmentation, trend isolation, data quality validation), the root cause you isolated, and the measurable operational outcome that followed—such as a denial rate drop, faster collection cycle, or revenue recapture.
Where people lose it: Candidates often describe building a dashboard or running a query without showing the analytical reasoning that turned data into a business decision—or they cite improvements they didn't directly drive. Avoid vague claims like 'improved financial performance' without naming a specific KPI and the percentage or dollar change.