Etenico Technologies
Website:
etenico.com
Job details:
Job Title
Lead Business Analyst – AI/ML, LLM & Healthcare Workflow Transformation
Job Summary
We are looking for a Lead Business Analyst to drive the business analysis, solution shaping,
and roadmap execution for AI/ML and LLM-powered products across payer and provider
workflows. This role will work closely with Product Management, Engineering, Data
Science, Clinical/Operations teams, and leadership to identify high-value use cases, define
scalable requirements, and ensure successful rollout of AI-enabled capabilities.
The ideal candidate should be strong in business analysis, healthcare workflow
understanding, Agile execution, stakeholder management, and AI solution translation.
This person should be capable of converting complex operational problems into clear
business requirements for solutions involving machine learning models, large language
models, intelligent document processing, workflow automation, RAG-based copilots,
and human-in-the-loop review systems.
Role Purpose
This role exists to ensure that AI initiatives are not handled as isolated technical experiments,
but as measurable business solutions that improve coding quality, productivity, turnaround
time, gap closure, and zero-touch automation outcomes across healthcare operations.
Key Roles and Responsibilities
1. Business Problem Discovery and AI Opportunity Identification
Partner with Product Managers, Operations leaders, SMEs, and client/business
stakeholders to identify high-impact problems suitable for AI/ML or LLM-based
solutions.
Conduct workshops, process walkthroughs, and current-state assessments to
understand pain points, workflow bottlenecks, decision gaps, and manual effort
drivers.
Convert business pain points into structured use cases, opportunity statements, and AI
solution hypotheses.
Evaluate use cases based on business value, feasibility, data readiness, model risk,
workflow fit, and implementation effort.
Help leadership prioritize roadmap items for short-term wins and long-term strategic
AI investments.
2. Requirements Definition for AI/ML and LLM Solutions
Translate business needs into clear functional requirements, non-functional
requirements, data requirements, workflow rules, and success metrics.
Prepare epics, features, user stories, use cases, business rules, decision trees,
acceptance criteria, and process maps.
Define requirements for AI-enabled scenarios such as:
o auto-coding
o code prediction assistance
o concurrent gap closure
o prospective suspecting
o quality/HEDIS gap identification
o document summarization
o evidence extraction
o workflow copilots
o intelligent exception routing
Document expected AI behavior including:
o input data sources
o output expectations
o confidence thresholds
o exception handling
o fallback logic
o human review paths
o audit trail needs
3. Healthcare Workflow and Domain Alignment
Support requirement definition across payer and provider workflows, including
retrospective, concurrent, and prospective programs.
Work with SMEs to map operational workflows, coding decisions, chart/document
flows, and intervention paths.
Ensure AI solutions align with healthcare business logic, coding policies, operational
controls, and regulatory expectations.
Collaborate with integration and platform teams on data exchange requirements
involving claims, clinical documents, EMR/EHR feeds, payer platforms, and
workflow systems.
Support domain translation for healthcare interoperability and data movement needs
such as APIs, FHIR, HL7, and related data validation requirements.
4. Collaboration with Product, Engineering, and Data Science
Serve as the primary bridge between business stakeholders and technical teams.
Work with architects, AI/ML engineers, and developers to translate business
requirements into implementable solution components.
Support definition of requirements for:
o ML model inputs/outputs
o prompt-driven workflows
o retrieval-based knowledge grounding
o business rules layered on model output
o human-in-the-loop review steps
o monitoring and feedback loops
Clarify requirements during grooming, sprint planning, development, testing, and
UAT.
Help teams make trade-off decisions across manual, rules-based, AI-assisted, and
fully automated approaches.
5. AI Evaluation, Validation, and Acceptance
Define business-centric validation approaches for AI outputs, workflow accuracy, and
operational usability.
Create acceptance criteria for both deterministic logic and non-deterministic AI
behavior.
Support testing of LLM-based solutions, chat/coplanar experiences, automation flows,
document extraction, and prediction accuracy.
Work with QA and SMEs to validate:
o business-rule adherence
o relevance of AI outputs
o hallucination/error scenarios
o edge cases
o workflow breakpoints
o confidence-based routing
Coordinate UAT and pilot sign-off with business teams.
6. Data, Reporting, and KPI Tracking
Define measurable business outcomes for every AI feature or release.
Partner with analytics teams to establish dashboards and reporting for operational and
AI performance.
Track KPIs such as:
o zero-touch automation rate
o coding productivity
o turnaround time reduction
o quality improvement
o chart-level precision/recall/accuracy where relevant
o user adoption
o review load reduction
o business throughput
Ensure traceability from business objective to requirement, feature, KPI, and release
outcome.
7. Agile Execution and Backlog Leadership
Own the BA function across multiple roadmap streams and ensure backlog readiness
for development teams.
Lead story refinement, requirement clarification, dependency management, and
release planning support.
Maintain alignment between roadmap objectives, release scope, and execution
priorities.
Proactively identify requirement gaps, delivery risks, stakeholder misalignment, and
change requests.
Support production rollout, release notes, business enablement, and post-release
feedback collection.
8. Stakeholder Management and Executive Communication
Communicate clearly with senior leaders, product heads, engineering teams,
operations teams, and clients.
Prepare concise business cases, decision notes, summary decks, and impact updates
for leadership reviews.
Present risks, assumptions, trade-offs, and recommendations in business language.
Support client-facing demonstrations, internal reviews, and roadmap discussions
where needed.
9. BA Team Leadership and Process Maturity
Guide and mentor Business Analysts supporting the roadmap.
Establish standard templates, requirement quality practices, AI solution
documentation patterns, and backlog governance.
Improve BA maturity in areas such as AI discovery, workflow redesign, story
decomposition, and structured UAT.
Drive consistency across initiatives while allowing flexibility for different product
and operational use cases.
Required Qualifications
Bachelor’s degree in Engineering, Computer Science, Business, Healthcare
Informatics, Life Sciences, or related field.
8+ years of experience in Business Analysis, with at least 2+ years in data, AI,
automation, analytics, or GenAI-related initiatives.
Strong experience in requirement gathering, business process analysis, Agile delivery,
stakeholder management, and UAT support.
Experience working with cross-functional teams including Product, Engineering, QA,
SMEs, and Operations.
Strong understanding of healthcare payer/provider workflows, operations, or
platform-based solution environments.
Ability to convert ambiguous business needs into structured, actionable requirements.
Strong written and verbal communication skills.
Preferred Qualifications
Experience in healthcare domains such as risk adjustment, medical coding, clinical
workflows, claims, utilization management, quality programs.
Exposure to AI/ML, LLM, NLP, RAG, workflow automation, or intelligent document
processing solutions.
Familiarity with SQL, dashboards, analytics tools, and API-based system integrations.
Working knowledge of FHIR, HL7, payer/provider platforms, or healthcare data
exchange concepts.
Experience using Jira, Azure DevOps, Confluence, Visio, Lucid chart, Miro, Power
BI, Tableau, or similar tools.
MBA, and AI-related certifications are a plus.
Click on Apply to know more.