The Role
The Claims Analytics Manager leads a team in analyzing healthcare claims, setting methodologies, and aligning with client goals to drive financial outcomes.
Summary Generated by Built In
Role OverviewThe Senior Manager, Claims Analytics, leads the claims analytics function within the Implementation organization. This role is responsible for overseeing complex reimbursement and payment accuracy analyses, managing analysts, setting analytical standards, and partnering cross-functionally with GTM, Customer Success, Product, and Engineering teams to ensure successful client implementations.This role combines deep healthcare claims expertise with people leadership, strategic thinking, and operational execution to scale analytics capabilities and drive measurable financial outcomes for clients.Key ResponsibilitiesLeadership & Strategy
- Lead and mentor a team of Implementation Claims Analysts, setting priorities, performance expectations, and development plans. Define and standardize analytical methodologies, reporting frameworks, and best practices for claims and reimbursement analysis.
- Partner with Implementation leadership to align analytics deliverables with client goals, timelines, and success metrics.
- Act as a subject-matter expert in claims analytics for complex or high-visibility client implementations.
- Oversee large-scale analysis of claims data related to charge capture, reimbursement, underpayment, overpayment, and payment accuracy.
- Ensure the delivery of exception-driven, actionable insights that clearly identify systemic versus isolated issues.
- Review and validate analytical outputs, ensuring accuracy, consistency, and clarity in reporting and client-facing deliverables.
- Guide analyses related to:
- Payor reimbursement behavior and trends
- RVU productivity and payment alignment
- Revenue cycle optimization opportunities
- Financial performance to benchmarks, goals, and norms
- Partner with GTM and Customer Success teams to support implementations, renewals, and expansion opportunities through analytics insights.
- Collaborate with Product and Engineering teams to influence roadmap priorities based on claims analysis findings and client needs.
- Serve as a senior analytics representative in client-facing discussions, executive readouts, and strategic reviews.
- Provide guidance on data ingestion and processing pipelines using SQL*Loader, Oracle, shell scripting, and cloud-based tools.
- Oversee advanced analytics leveraging SQL, PL/SQL, Python, Scala, Spark, and AWS.
- Ensure scalable, repeatable approaches to analyzing billions of claims records across clients.
- 8+ years of experience in healthcare claims analytics, payment accuracy, or reimbursement analysis.
- Prior experience working with claims editing or payment accuracy vendors.
- Strong expertise in medical coding, billing guidelines, and reimbursement methodologies.
- Proven people leadership experience managing and developing analytics teams.
- Advanced proficiency in SQL and experience working with large healthcare datasets.
- Strong executive communication and presentation skills.
- Strategic thinking with a strong bias toward execution
- Ability to lead through ambiguity and change
- High accountability and ownership mindset
- Strong client-facing presence and stakeholder management skills
- Passion for building scalable analytics capabilities and high-performing teams
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The Company
What We Do
We’re on a mission to make healthcare more efficient. We’re empowering healthcare payers and providers with next generation technology that will reduce administrative burden, help them focus on delivering better care, and improve the entire system. Rialtic was launched and built by a team of seasoned industry veterans and deep technology and product experts. We understand the challenges faced by payers and have built a solution from the ground up to serve our customers. Healthcare is complex. By creating efficiency, saving money, and enabling new capabilities, the Rialtic platform will free up payers and providers to focus on their members and patients. We'll solve the rest.
