Data Mining 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 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. **What You’ll Do:** - 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. **What You Bring:** - 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. **What We Offer:** - Work from anywhere in the US! Machinify is digital-first. - Top Medical/Dental/Vision offerings - FSA/HSA - Tuition reimbursement - Competitive salary, 401(k) with company match - Additional health and wellness benefits and perks - Flexible and trusting environment where you’ll feel empowered to do your best work The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. **Pay range: $80,000 - $90,000** **Equal Employment Opportunity at Machinify** We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at: