Sr Healthcare AI Business Analyst

Overview

Job Title: Sr Business Analyst - Healthcare AI StrategyLocation: Hybrid - Atlanta, GA 

Job Type: Independent Contract (Contractor / Non-Employee)Start Date: October 19th

Pay Rate: $75-$95 per hour (1099/C2C)

Contract Length: 5 months

 

**Employment in this role is conditional upon successful execution of the contract by the client.**

 

We are seeking an experienced IT Business Analyst to drive the comprehensive requirements gathering, discovery phase, and baseline prioritization framework for our enterprise-wide Artificial Intelligence Transformation Strategy. The selected candidate will act as the principal architectural bridge between Client’s clinical, administrative, and financial operational executives and advanced data science engineering teams. The absolute core objective of this mandate is executing deep executive discovery and structured technical workshops to synthesize unstructured organizational pain points into an actionable, multi-year AI investment roadmap.

Responsibilities

Scope of Work: Leadership & Domain Expert Discovery

The Business Analyst will plan, architect, and conduct structured interviews and collaborative workshops with senior leaders and domain subject-matter experts (SMEs). These high-level sessions are designed to:

• Map Enterprise KPI Ecosystems: Understand discrete organizational goals, key performance indicators (KPIs), and targeted measures of success native to each leadership vertical.
• Isolate Operational Blockers: Explicitly identify operational, clinical, financial, and administrative challenges impeding the execution of core strategic objectives.
• Audit Optimization Target Baselines: Document existing transformation targets, including current cost reduction initiatives, workforce optimization mandates, productivity metrics, and revenue enhancement targets.
• Inventory Leverageable Assets: Audit and document active resources capable of being deployed for immediate AI optimization, including unallocated financial capital, human resources, data pipelines, and infrastructure capabilities.
• Proactively Introduce Proven Benchmarks: Inject and present contextualized, high-viability AI investment opportunities derived from successful implementations at peer Academic Medical Centers and leading health systems.
• Capture Qualitative Visions: Formalize leadership's specific perspectives on where AI models (generative, predictive, analytical) can maximally optimize clinical outcomes, operational efficiency, and end-user experiences.
• Build Discovery Governance Pipelines: Pinpoint key downstream stakeholders, workflow/process owners, and data SMEs critical for subsequent detailed discovery work and robust business case modeling.
• Evaluate Organizational AI Readiness: Assess operational departments for AI adoption readiness, explicitly identifying executive champions, anticipated pockets of cultural friction, and change-management speed factors.

Deliverables & Prioritization Framework Architecture

The ultimate objective of the requirements gathering phase is to facilitate the formulation of a unified, prioritized AI Investment Opportunity Inventory. The Analyst is responsible for structuring and populating an explicit prioritization taxonomy divided into three distinct operational tiers:

• Tier 1: AI Quick Wins: Initiatives capable of immediate tactical execution leveraging existing personnel, current data structures, and in-house enabling technologies, requiring minimal capital allocation.
• Tier 2: Deep Discovery Opportunities: Strategic use cases displaying high potential ROI but requiring specialized, secondary deep-dive discovery, target architecture mapping, and complex business-case modeling.
• Tier 3: Capital Planning Pipeline: High-impact, enterprise-transformative AI investments slated for formal budget submission through the AI Strategy Capital Planning Process or specific departmental capital allowances.

Qualifications

Candidate Qualifications & Operational Requirements

• Healthcare Expertise: 5+ years of progressive IT Business Analysis experience, with a heavy preference for individuals who have executed enterprise strategy mandates within a matrixed multi-hospital healthcare system.
• AI/ML Domain Literacy: Proven understanding of data science principles, machine learning lifecycles, structured vs. unstructured data ingestion, natural language processing (NLP), Large Language Models (LLMs), a