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Salary: USD 64,832 - 85,092 / annual
Oscar Health is seeking a Senior Analyst, Payment Integrity Disputes to join the Disputes team. In this role, you will be responsible for supporting payment integrity disputes and issue resolution within Oscar's claim environment. You will scope, triage, investigate, and execute on solutions and process improvements, leveraging deep understanding of Oscar's claim infrastructure, workflows, tooling, platform logic, and data models.
Key responsibilities include serving as a subject matter expert on Oscar reimbursement policies, payment integrity disputes, and claims processing edits. You will respond to internal and external inquiries regarding policies and edits, research industry-standard coding rules, and provide input into reimbursement policy language. You will use insights from claims review and data analysis to identify payment integrity opportunities and translate them into business requirements for cross-functional collaboration.
You will ingest information from internal and external partners regarding adverse claim outcomes, collaborate to scope and prioritize items, and deliver solutions. Working proactively with the team, you will identify thematic areas of opportunity using partner submissions, data mining, and process monitoring. You will maintain transparency and collaboration by keeping stakeholders informed of progress, status changes, and blockers. Additionally, you will support Oscar's operational objectives by providing research, root cause analysis, and training when leadership escalates issues.
The role requires 4+ years of experience in claims processing, coding, auditing, or healthcare operations, with 3+ years in medical coding and current certification (CPC, COC, CCS, RHIT, or RHIA). You should have 2+ years deriving business insights from datasets, 1+ year improving business workflows, and 1+ year collaborating with stakeholders. Experience with reimbursement methodologies, provider contracts, and claims processing practices is essential. Bonus qualifications include technical or process improvement background, SQL proficiency, and experience with large datasets.
