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Business, Tech & Metrics Improvement SME – Provider Lifecycle Management (AI-First Consulting)
Role Overview
We are seeking a Business, Tech & Metrics Improvement SME – Provider Lifecycle Management (PLM) for our Healthcare Consulting practice. As an AI-first organization, we partner with healthcare enterprises, Health Plans, and Health Systems to modernize operations via AI, engineering, and data.
Requires deep expertise across PLM: Provider Network Management, Credentialing, Contracting, Primary Source Verification (PSV), Enrollment, Onboarding, Directory Management, and Data Architecture. You will lead engagements, conduct AI-led assessments, design target architectures, and drive metric improvements to optimize performance, lower costs, and reduce onboarding speed from months to days.
Key Responsibilities
AI-Led Diagnostics & Operational Assessments
Assess clients' PLM ecosystems, evaluating processes, tech architecture, data governance, and bottlenecks.
Use AI, ML, and process mining to analyze workflow latency, data leaks, and handoff inefficiencies.
Benchmark against metrics, standards, and regulations (NCQA, URAC, CMS, No Surprises Act).
Deliver blueprints, ROI models, and transformation roadmaps for AI modernization.
PLM Domain & Business Optimization
Serve as SME across PLM: PDM, Credentialing/Re-credentialing, CAQH, Contracts, Directory Accuracy, and Portals.
Architect onboarding journeys eliminating manual entry, streamlining PSV, and automating rosters.
Enforce data quality for provider MDM, SSOT models, NPI lookups, and taxonomy while ensuring compliance.
Tech Improvement & AI Solution Design
Partner with engineering/data science teams to build AI-first PLM tools
Architect GenAI/LLM solutions for contract parsing, NLP for rosters/docs, and OCR for credentialing.
Design API strategies connecting PLM with CAPS (Facets/QNXT), EHRs, CAQH, NPDB, and Salesforce Health Cloud.
Establish AI governance, human-in-the-loop (HITL) handling, and data validation guardrails.
Performance Metrics & Operational Engineering
Track And Optimize Core PLM Metrics
Time-to-Network: Reduce onboarding from 90–120 days to <14 days
Touchless Automation: Maximize straight-through processing for rosters and PSV.
Directory Accuracy: Elevate to >98% for No Surprises Act compliance.
Cost & CSAT: Lower unit costs and improve provider satisfaction.
Work arrangement
No
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