Sr. Manager, Reimbursement Operations & Optimization

We are seeking a highly skilled and experienced Senior Manager, Reimbursement Operations & Optimization to lead high impact initiatives that improve financial & operational performance across the revenue cycle. In partnership with operational leaders, this role will be focused on designing, implementing, and scaling end to end reimbursement processes to drive sustainable improvements in reimbursement (i.e., improve ASP through reducing initial denial rate, appeal efficacy, etc) and operational efficiency.

Success in this role requires deep expertise in medical reimbursement systems and processes (e.g., utilization management, adjudication, and operational systems), along with strong knowledge of payor claim and medical policies to optimize reimbursement. Analytical, interpersonal, and operational skills are critical to streamlining processes and improving financial performance. A solid understanding of payor claim and appeal review processes—particularly from a claim processing and medical policy perspective—will also be essential to driving effective process improvements.

• Regularly analyze revenue cycle data to gauge and optimize operational performance; use data to identify reimbursement leakage and variability to maximize payor performance and operational outcomes. 
• Design scalable, system-based solutions to address root causes rather than symptoms in a way that will measurably improve operational effectiveness and claims performance. 
• Produce clear problem statements, process maps, business requirements, success metrics, and post implementation performance reviews to address root causes. 
• Monitor & track Payor Performance to maximize reimbursement, partnering with internal operations leaders on reviews (i.e., met coverage policies), remediations and payor escalations (if/when needed). 
• Leverage data to identify trends, forecast impact, and prioritize high‑ROI initiatives, delivering clear, insights and recommendations to senior leadership & cross-functionally. 
• Take a proactive role in evaluating and implementing revenue cycle technologies (OCR, AI-Enabled workflows, integrations, automations, et al.) to enhance operational effectiveness 
• Play a key role in revenue cycle technology initiatives, helping translate operational needs into requirements, partnering with technical teams in design and build, ensuring successful UAT to maximize production readiness and owning the creation of business documentation (requirements, process flows, UAT artifacts) 
• Partner with Reimbursement leaders to re‑engineer reimbursement workflow to standardize processes while preserving flexibility for payor‑specific nuances. 
• Drive cross functional workstreams across finance, operations, clinical teams, and Customer Care, to optimize revenue cycle performance. 

• 8+ years of experience in healthcare reimbursement, revenue cycle operations, or related financial operations, with progressive leadership responsibility.
• Demonstrated success driving process improvement and reimbursement optimization initiatives with measurable financial impact.
• Strong understanding of payor dynamics, prior authorization, claims adjudication, denials, and appeals.
• Experience leading or partnering with automation, AI, or technology enabled operational transformations.
• Advanced analytical skills with the ability to translate complex data into actionable insights.
• Proven ability to lead cross functional initiatives in a fast paced, ambiguous environment.
• Excellent analytical skills with the ability to analyze complex data, identify trends, and make data-driven decisions.  
• Experience building a strong team. Knows how to screen, hire, and coach new team members during periods of high growth.

Preferred Qualifications:

• Clinical Background (BSN, Genetic counseling, etc.) a plus but not required. 
• Experience in diagnostics, laboratory services, or complex reimbursement environments. 
• Formal training or certification in Lean, Six Sigma, or process improvement methodologies. 
• Experience building early indicator KPI models that forecast long-term reimbursement outcomes.

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