Senior Business System Analyst

• Solicit, review and analyze business requirements
• Write business and technical requirements
• Communicate and validate requirements with stakeholders
• Validate solution meets business needs
• Work with application users to develop test scripts and facilitate testing to validate application functionality and configuration
• Participate in organizational projects and/or manage small/medium projects related to assigned applications
• Translates customer needs into quality system solutions and ensures effective operational outcomes
• Focus on business value proposition*Apply understanding of 'As Is' and 'To Be' processes to develop solution
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment).

• Role Focus Areas:

• Core Expertise Required:

• Provider Management
• Utilization Management
• Care Management

• Domain Knowledge:

• Value-Based Care
• Clinical & Care Management
• Familiarity with Medical Terminology
• Experience with EMR (Electronic Medical Records) and Claims Processing

• Technical/Clinical Understanding:

• Admission & Discharge Processes
• CPT Codes, Procedure Codes, Diagnosis Codes

Job Qualification:

Undergraduate degree or equivalent experience.

Minimum 5 Years experience in Business Analysis in healthcare including providing overall support, maintenance, configuration, troubleshooting, system upgrades, and more for Healthcare Applications.

Good experience on EMR / RCM systems

Demonstrated success in running EMR / RCM / UM, CM and DM systems support in requirements, UAT, deployment supports

Experience working with stakeholders, gathering requirements, and taking action based on their business needs

Proven ability to work independently without direct supervision

Proven ability to effectively manage time and competing priorities

Proven ability to work with cross-functional teams

Core AI Understanding

AI/ML Fundamentals: Understanding of supervised, unsupervised, and reinforcement learning.

Model Lifecycle Awareness: Familiarity with model training, evaluation, deployment, and monitoring.

Data Literacy: Ability to interpret data, understand data quality issues, and collaborate with data scientists.

AI Product Strategy

AI Use Case Identification: Ability to identify and validate AI opportunities aligned with business goals.

Feasibility Assessment: Understanding of whats technically possible with current AI capabilities.

AI/ML Roadmapping: Planning features and releases that depend on model development cycles.

Collaboration with Technical Teams

Cross-functional Communication: Ability to translate business needs into technical requirements and vice versa.

Experimentation & A/B Testing: Understanding of how to run and interpret experiments involving AI models.

MLOps Awareness: Familiarity with CI/CD for ML, model versioning, and monitoring tools.

AI Tools & Platforms

Prompt Engineering (for LLMs): Crafting effective prompts for tools like ChatGPT, Copilot, or Claude.

Responsible AI & Ethics

Bias & Fairness: Understanding of how bias can enter models and how to mitigate it.

Explainability: Familiarity with tools like SHAP, LIME, or model cards.

Regulatory Awareness: Knowledge of AI-related compliance (e.g., HIPPA, AI Act).

AI-Enhanced Product Management

AI in SDLC: Using AI tools for user story generation, backlog grooming, and documentation.

AI for User Insights: Leveraging NLP for sentiment analysis, user feedback clustering, etc.

AI-Driven Personalization: Understanding recommendation systems, dynamic content delivery, etc.