Lead AI-led assessments and diagnostics of Provider Lifecycle Management processes, technology, data, and operational performance.
Provide deep domain expertise across Provider Network Management, Credentialing, Re-credentialing, Contracting, PSV, Enrollment, Onboarding, and Directory Management.
Analyze existing PLM workflows to identify process bottlenecks, manual activities, data gaps, and operational inefficiencies.
Use AI/ML, GenAI, process mining, and analytics to identify opportunities for automation and process improvement.
Design optimized provider onboarding and lifecycle journeys to reduce turnaround time and manual intervention.
Drive improvements in Provider Data Management (PDM), Provider MDM, data quality, SSOT, NPI, taxonomy, and provider directory accuracy.
Work with technology and engineering teams to design AI-first PLM solutions and target architectures.
Define use cases for GenAI/LLMs, NLP, OCR, document processing, contract parsing, credentialing automation, and roster automation.




Develop API and integration strategies connecting PLM platforms with Facets, QNXT, EHRs, CAQH, NPDB, Salesforce Health Cloud, and other healthcare systems.
Establish AI governance, human-in-the-loop (HITL), data validation, security, and compliance guardrails.
Define and monitor PLM KPIs including Time-to-Network, Time-to-Credential, Straight-Through Processing, Directory Accuracy, Cost per Provider, and Provider CSAT.
Benchmark processes against NCQA, URAC, CMS, No Surprises Act, and relevant healthcare industry standards.
Develop business cases, ROI models, transformation roadmaps, process blueprints, and target operating models.
Partner with business, technology, data science, and engineering stakeholders to deliver measurable transformation outcomes.
Identify prospects to reduce provider onboarding timelines from months to days, increase automation, reduce operational costs, and improve provider experience.

📌 Business Analyst Healthcare Plm Contract Hyderabad (India)
🏢 Saaki Argus And Averil Consulting
📍 India