Central Automation CoE | IQVIA
Role Summary
Lead a team of Business Analysts within IQVIA's Central Automation CoE to deliver automation and AI value across multiple BUs and regions. Own portfolio management, people leadership, process/methodology stewardship, and project/delivery oversight. Ensure rigorous ADLC (AI/Automation Development Life Cycle) execution with Lean discovery, measurable ROI/FTE savings, and audit-ready documentation. Provide functional leadership for AI and agentic automation initiatives, including use-case discovery, solution feasibility, responsible AI considerations, human-in-the-loop controls, and business value realization.
Key Responsibilities
1 · Portfolio Management & Governance
Own the BA portfolio across BUs/regions; manage intake via VIA/ServiceNow; maintain pipeline in Smartsheet; link Process IDs across Smartsheet, JIRA, and PSA.
Partner with PMO on prioritization, capacity planning, and benefits tracking (ROI, FTE savings, cycle-time KPIs).
Lead governance cadences: Weekly/Biweekly pipeline & delivery reviews, Monthly BU governance, and Quarterly sponsor reviews.
Balance per-BA workload (~10-12 projects); resolve cross-team dependencies and bottlenecks.
2 · People Leadership
Manage and coach BAs/Sr. BAs: goal-setting, performance management, feedback, and career development.
Drive upskilling on Lean, ADLC, tools (Power Automate, Alteryx, Python/SQL) and GenAI/agentic technologies (Copilot, Cursor, LangGraph) including prompt engineering, retrieval-augmented generation (RAG), AI agent orchestration, AI-assisted requirements development, and responsible AI practices.
Allocate resources effectively; support hiring, onboarding, and stretch opportunities.
Foster a team culture of client focus, collaboration, ownership, and innovation.
3 · Process & Methodology (ADLC / Lean)
Define and continuously improve BA standards, templates, and repositories (BRD, PDD, TFD, SDD; SharePoint/Confluence).
Embed ADLC end-to-end: Intake → L0/L1/L2 Discovery → Technical Discovery → Business Case → Build → UAT → Rollout.
Maintain RACI, single approval flow, prioritization criteria, and evidence-based traceability.
Run retrospectives; sustain continuous improvement and team playbooks.
Establish AI-specific BA standards covering problem framing, use-case suitability, prompt and knowledge-source requirements, model/agent evaluation criteria, human oversight, explainability, output validation, and post-deployment monitoring.
4 · Project & Delivery Oversight
Assure discovery quality and gate readiness; lead Go/No-Go decisions with clear acceptance criteria.
Oversee RAID management, change control (Major >16 hrs / Minor Align environments, access, data security, and governance with Architects and PMO.
Ensure user stories, non-functional requirements, and traceability matrices are complete and testable.
For AI solutions, ensure requirements address data and knowledge-source quality, hallucination and accuracy risks, prompt security, access controls, human-in-the-loop review, evaluation metrics, and responsible AI governance.
5 · Business Analysis & Solution Enablement
Drive robust business cases (effort, FTE, ROI, payback period) with PMO/Finance inputs via PSA.
Produce current/future-state process maps and L0/L1/L2 assessments; validate automation feasibility and value.
Support tool selection (RPA/Power Automate, Alteryx, Python/SQL, OCR, GenAI); assess API/GUI integrations.
Translate business needs into AI-ready requirements, including user journeys, prompt workflows, knowledge and data requirements, grounding/RAG needs, agent roles, orchestration logic, exception handling, human approval points, and measurable evaluation criteria.
Assess the suitability of deterministic automation, predictive AI, generative AI, and agentic AI approaches based on process complexity, data availability, risk, scalability, and expected business value.
Maintain full traceability from BRD/PDD through test coverage and production KPIs.
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