Tasks & Duties:
Lead workshops with business stakeholders to document business processes, pain points, user stories, functional specifications, and acceptance criteria.
Perform feasibility analysis to identify opportunities for AI/ML, automation, decisioning, and workflow optimization.
Develop process maps (BPMN), system flows, data lineage, and integration documentation.
Translate business requirements into clear, actionable technical specifications, including APIs, data flows, validation rules, and model inputs/outputs.
Analyze existing applications, databases, integrations, and AWS cloud environments to inform solution design and implementation.
Collaborate closely with architects, developers, data scientists, and engineers to ensure accurate interpretation of requirements and solution intent.
Work with data science and engineering teams to define data needs, metrics, business rules, validation logic, and AI/ML model behavior.
Lead and support AI pilots and POCs, including defining success metrics, tracking outcomes, and documenting lessons learned for scale-up.
Conduct root cause analysis and recommend improvements to accuracy, efficiency, compliance, and user experience.
Support dashboarding, analytics KPIs, and reporting for business and executive leadership.
Support User Acceptance Testing (UAT), traceability, defect triage, and business sign-offs.
Partner with QA teams to ensure robust testing coverage across multiple business and edge scenarios, especially for AI-driven solutions.
Act as a liaison between business program areas, IT delivery teams, vendor partners, and technical SMEs to ensure alignment and clarity.
Produce regular status updates, technical documentation, and executive-level summaries on progress and outcomes.
Support training, SOP updates, knowledge transfer, and production rollouts.
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