AI Analyst With Healthcare Background

Role: AI Analyst with Healthcare Background
Location: Woodland Hills, CA(3 times a week)
Contract Type: W2

Mandatory –

1. Consultants local to Los Angeles area
2. Commute three times in a week to Woodland Hills office
3. Diverse nationality consultants
   
   Job Description:
   seeking an experienced Artificial Intelligence & Machine Learning (AI/ML) Systems Analyst to bridge the gap between business stakeholders, data scientists, AI/ML engineers, and technology teams. This role will be responsible for analyzing business problems, defining AI/ML solution requirements, evaluating data readiness, supporting model implementation, and ensuring AI solutions align with business objectives, regulatory requirements, and enterprise governance standards. The ideal candidate will possess strong analytical skills, healthcare domain knowledge, and experience working with AI, machine learning, and Generative AI technologies.

Key Responsibilities

Business & Systems Analysis

• Collaborate with business stakeholders to identify opportunities for AI/ML-driven process improvements and automation.
• Elicit, analyze, and document business, functional, and non-functional requirements.
• Create user stories, process flows, use cases, data mappings, and acceptance criteria.
• Translate business requirements into AI/ML solution specifications.
• Support backlog grooming, sprint planning, and Agile delivery processes.

AI/ML Solution Analysis

• Partner with AI/ML engineers and data scientists to define model objectives and success metrics.
• Analyze data sources and determine data quality, completeness, and readiness for AI initiatives.
• Support predictive analytics, recommendation systems, NLP, GenAI, and intelligent automation initiatives.
• Evaluate AI model outputs and assist with validation, testing, explainability, and business adoption.

Data & Analytics

• Perform data analysis using SQL, Python, Power BI, and reporting tools.
• Develop dashboards and reporting mechanisms to monitor AI model performance and business outcomes.
• Support data governance, lineage, quality, and compliance activities.
• Assist in feature identification and business rule definition for ML models.

AI Governance & Compliance

• Ensure AI solutions comply with enterprise AI policies, security standards, and regulatory requirements.
• Support documentation of model governance, auditability, explainability, and risk assessments.
• Participate in AI solution reviews, testing, and deployment readiness activities.

Stakeholder Engagement

• Act as a liaison between business teams, product owners, architects, data engineers, and AI/ML engineers.
• Communicate findings, recommendations, and project status to leadership and project stakeholders.
• Facilitate workshops, requirement sessions, and solution reviews.

Required Qualifications

Education

• Bachelor's degree in Computer Science, Information Systems, Data Science, Artificial Intelligence, Engineering, Mathematics, or a related field.
• Master's degree preferred.

Experience

• 5+ years of Systems Analysis, Business Analysis, Product Analysis, or related experience.
• 2+ years supporting AI/ML, Advanced Analytics, Data Science, or Generative AI initiatives.
• Experience working within Agile/Scrum delivery environments.
• Healthcare, insurance, or regulated industry experience preferred.

Technical Skills

• SQL and relational databases
• Python or R for analytics
• Power BI, Tableau, or equivalent reporting tools
• Machine Learning concepts and model lifecycle understanding
• Generative AI, LLMs, Retrieval-Augmented Generation (RAG), and prompt engineering concepts
• Cloud platforms such as Azure, AWS, or GCP
• Azure AI Services, Azure Machine Learning, or equivalent AI platforms preferred 

Preferred Skills

• Healthcare benefits, claims, member, provider, or utilization management domain knowledge.
• Experience with AI governance frameworks and responsible AI practices.
• Understanding of MLOps concepts, model monitoring, and deployment processes.
• Knowledge of NLP, Computer Vision, Predictive Analytics, and Agentic AI architectures.
• Familiarity with Jira, Azure DevOps, Confluence, and Git-based development workflows.
  
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