Data Mining Sr. Analyst

Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.

Machinify is seeking a Senior Analyst to lead the development and refinement of new reimbursement and payment integrity concepts. This is a hands-on healthcare domain role, not a technical or engineering position. The ideal candidate understands reimbursement logic, payment policies, and provider contracts in depth — and can translate that expertise into clear, structured concepts that inform analytics and automation efforts. 

You will be focused on discovering where and why payment errors occur, designing methods to detect and prevent them, and partnering with technical teams to operationalize your findings. This role is ideal for someone who loves digging into claims data, identifying systemic payment issues, and shaping how technology solutions capture real-world reimbursement logic. 

• Lead pre and post-pay claim reviews to identify inaccurate payments using reimbursement and contract expertise.
• Analyze and interpret provider contracts to ensure payments align with negotiated terms, methodologies, and payer rules.
• Collaborate closely with engineering and data science teams to translate business and reimbursement logic into analytical and automation frameworks.
• Research and document emerging reimbursement and contract patterns, coverage rules, and billing practices to inform concept development.
• Translate complex reimbursement and contract scenarios into structured rules and business logic for implementation.
• Analyze claim-level data to pinpoint root causes of overpayments or incorrect denials and recommend corrective approaches.
• Maintain expertise on CMS and commercial payer reimbursement guidelines.
• Support quality review, concept validation, and process improvement initiatives.