Business Analyst – Provider Credentialing (AI-Enabled Healthcare Platforms)

Atlas Systems•East Brunswick, NJ

1d•Remote

About The Position

We are seeking a highly experienced Business Analyst with deep domain expertise in Provider Credentialing and strong working knowledge of AI-enabled product design to lead a defined, outcome-driven engagement . The objective of this role is not to design “another credentialing system,” but to reimagine provider credentialing using AI, automation, and intelligent workflows —while remaining grounded in real-world payer and provider operations. This role owns the functional vision end-to-end: Conceptualizing disruptive, AI-assisted workflows Designing high-fidelity Figma UI/UX Translating the solution into engineering-ready user stories and documentation

Requirements

Provider Credentialing Domain Expertise (Must-Have)
Deep, hands-on experience with:
Health System credentialing operations
Health Plan / payer credentialing workflows
Primary Source Verification (PSV)
Regulatory and compliance considerations
Prior involvement in credentialing platforms, provider data management, or payer/provider operational systems.
AI & Intelligent Systems Acumen ( Must-Have )
Strong working knowledge of:
AI/ML-enabled enterprise products
Generative AI and intelligent automation concepts
Ability to:
Identify where AI creates real operational leverage
Avoid “AI for AI’s sake”
Design explainable, compliant, and auditable AI-assisted workflows
UX, Product & Technical Skills
Proven experience designing enterprise-grade UX in Figma
Strong product thinking—able to connect business outcomes to UX and system behavior
Comfortable interpreting API specifications and mapping them to workflows
Experience working with agile engineering teams for clean handoff
8+ years as a Business Analyst / Product Analyst / Product Manager in healthcare technology
Experience spanning:
Payers and provider organizations
Platform or product-led healthcare solutions

Nice To Haves

Experience collaborating with data science or AI engineering teams is a strong plus.
Prior exposure to AI-enabled healthcare platforms preferred

Responsibilities

AI-Forward UX & Workflow Design Design high-fidelity Figma screens that depict:
Provider credentialing workflows for Health Systems
Provider credentialing workflows for Health Plans
Reimagine traditional credentialing processes using:
AI-assisted data ingestion and normalization
Intelligent task prioritization and exception handling
Reduced manual touchpoints and “zero-click” workflows where feasible
Cover core and advanced use cases:
Initial credentialing and onboarding
Re-credentialing and continuous monitoring
Primary Source Verification (PSV)
Delegated credentialing
Exception handling, expirations, and audit readiness
Clearly model:
Human-in-the-loop vs AI-driven decisions
Confidence scoring, explainability, and review flows
Alerts, recommendations, and proactive interventions
Disruptive Use Case Definition Identify opportunities where AI can materially change :
Time to credential
Cost per provider
Manual effort and rework
Audit and compliance burden
Ensure the solution:
Goes beyond digitizing existing workflows
Challenges legacy assumptions in credentialing operations
Differentiates clearly from incumbent credentialing platforms
Functional & Business Documentation Produce engineering-ready artifacts , including:
End-to-end use cases and workflow narratives
User stories with clear acceptance criteria
Functional requirements mapped to UI and AI behaviors
Edge cases, fallback scenarios, and exception handling
Clearly document:
Where AI augments human decision-making
Where deterministic rules still apply
Guardrails for compliance, accuracy, and auditability
API, Data & Intelligence Flow Interpretation Review and interpret API documentation from primary credentialing data sources (e.g., CAQH, NPI, state boards, sanctions, exclusions)
Identify and document:
Which APIs are invoked at each stage of the workflow
Event-driven vs on-demand data pulls
How AI layers consume, enrich, and reason over source data
Partner with engineering to ensure AI concepts are implementable , not theoretical.