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Abacus Insights is a data and AI platform for payer intelligence, backed by $100M in funding, transforming how health plans use data to improve outcomes and reduce costs. The company helps health plans break down data silos to create a single, trusted data foundation powering better decisions across care and cost management.
You will serve as the payer-operations expert and individual contributor on client engagement teams launching new and expanded service offerings for health plans. This role spans medical and pharmacy claims, utilization management, benefits administration, quality improvement, provider performance, contracting, and regulatory compliance.
Your responsibilities include:
• Serve as the Payer Business Domain Subject Matter Expert on client engagement teams, acting as the go-to authority for health plan clients across payer operations: claims, utilization, benefits, quality, provider performance, and network strategy.
• Advise clients on quality improvement (HEDIS, STAR ratings) and provider performance management—identifying gaps, root causes, and improvement plans across cost, quality, access, and network metrics.
• Provide counsel on contracting and network strategy (value-based, risk-sharing, fee-for-service, total-cost-of-care models) and support provider performance reviews, JOCs, and regulatory compliance (state, federal, NCQA) with data-driven recommendations.
• Analyze medical, pharmacy, financial, and provider performance data to surface actionable insights and trends across clients' book of business.
• Build and maintain BI reporting tools, dashboards, and AI-enabled analytics that give clients visibility into performance trends, risks, and opportunities; design customized reporting strategies that streamline and automate payer operations workflows.
• Partner with Product, Engineering, and Data/Analytics teams to translate payer domain requirements into technical specifications and bring client/market insights back to Product to inform roadmap priorities.
This is a hands-on role where you'll turn dense claims, quality, and provider performance data into dashboards, agents, and reporting that ship live within the engagement window—not just recommendations. You'll work inside the client's environment alongside the Engagement Manager, Data/Platform Engineers, AI Engineers, and QA, and feed what you learn back into the data engineering Center of Excellence as new offerings grow.
REQUIREMENTS:
• 7+ years of experience in healthcare payer operations, managed care, or health plan performance, including 5+ years of direct provider-facing experience with demonstrated success improving provider performance across cost and/or quality metrics.
• Deep, hands-on experience analyzing medical, pharmacy, financial, and provider performance data to identify trends and cost drivers.
• Proficiency in Power BI, SQL, and/or Tableau (or similar AI-enabled reporting tools), with a track record of building reporting tools that drive measurable business outcomes.
• Working knowledge of quality measurement frameworks (HEDIS, STAR ratings) and NCQA, state, and federal regulatory compliance requirements.
• Exposure to payment integrity or other adjacent payer analytics domains.
• Strong provider relationship management, communication, and influencing skills—comfortable leading structured performance conversations and driving accountability for outcomes.
• Ability to work independently, solve complex problems, and drive results in ambiguous, cross-functional situations, translating technical analysis into clear recommendations for executives, providers, and clients alike.
NICE-TO-HAVE:
• Experience supporting NCQA accreditation processes or state/federal quality and compliance audits.
• Experience negotiating provider contracts or administering government health plan contracts (e.g., state Medicaid), and/or experience with value-based or risk-based payment models and network optimization.
• Experience partnering with Product/Engineering teams in an Agile environment, including documenting technical and functional requirements.
• Exposure to AI or agent-based automation tools, or comfort partnering closely with engineers configuring analytics and reporting logic inside a cloud data platform (Snowflake, Databricks).
