Data Mining Analyst

Machinify is seeking an Analyst to help develop and refinement 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.
• 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.

• 2+ years of experience in healthcare data mining or claims editing on the provider, payer, or vendor side.
• Deep understanding of provider contracts, including rate structures, carve-outs, and reimbursement methodologies.
• Strong knowledge of claims processing, coding, billing, and payment logic across CMS and commercial payers.
• Proven ability to identify improper payment patterns, root causes, and opportunities for correction.
• Strong investigative and deductive reasoning skills; able to connect policy, data, and contractual details.
• Comfortable working in close collaboration with technical teams to guide implementation of business logic.
• Self-directed, detail-oriented, and adaptable to a fast-paced, growing environment.