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# Principal Data Scientist- CXI Agentic AI & Analytics discovery

- **Company:** HCL GLOBAL
- **Location:** Atlanta, GA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Machine Learning, Agentic-AI, Information Technology
- **Published:** November 7, 2026
- **Apply:** https://www.thejobnetwork.com/job/e0950fd1-f64e-4557-9b34-09dbac69c7b0/principal-data-scientist-cxi-agentic-ai-analytics-discovery

## About the Role

machine learning, advanced analytics, data science,-12 Yrs of Exp -
AI or AI transformation leadership - 5 Yrs of Exp -
healthcare payer, claims, member experience, G&A, audit, or regulatory workflow exposure -3 Yrs of Exp -
AI strategy, ML/AI use cases -5 Yrs of Exp -, * 12 years in AI, machine learning, advanced analytics, data science, or AI transformation leadership.

 * Healthcare domain experience is required, with healthcare payer, claims, member experience, G&A, audit, or regulatory workflow exposure preferred based on track assignment.
 * Master's or PhD in Data Science, AI, Computer Science, Statistics, or related field preferred.
 * Experience defining AI strategy, ML/AI use cases, data readiness, governance, and analytics roadmaps.
 * Healthcare payer, process mining, automation, or agentic AI experience preferred. Key Competencies /

Deliverables Competencies: AI strategy, agentic AI roadmap, advanced analytics, process mining leadership, AI governance, executive advisory, opportunity prioritization. Primary deliverables: AI opportunity framework, process mining direction, use case prioritization, agentic roadmap, AI governance inputs, executive summary.

## Description

* Define the AI discovery strategy and identify high-value agentic AI opportunities across CXI discovery tracks. * Guide process mining, analytics, data readiness assessment, and use case prioritization efforts.
 * Develop agentic AI solution roadmap concepts, implementation considerations, governance needs, and success measures.
 * Partner with business, architecture, and delivery teams to validate feasibility, value, risk, and adoption considerations.
 * Prepare executive-level AI findings, opportunity narratives, and roadmap recommendations.