Manager, Business Systems Analyst

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 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. 6 · Stakeholder Engagement & Communications • Build trusted relationships with BU leaders, SMEs, Architects, and development teams across global time zones. • Facilitate workshops, executive readouts, and governance forums; manage expectations and escalations. • Standardize portfolio/delivery reporting (Power BI); champion CoE ways of working. • Drive benefits realization tracking and coordinate smooth handovers to operations. Required Qualifications • Bachelor's degree in Business, Information Systems, Engineering, or related field • 6-8+ years in Business/Systems Analysis, Automation, or Digital Transformation • 3+ years leading Business Analysts or cross-functional delivery teams • Proven end-to-end ADLC delivery: Intake → L0/L1/L2 → BRD/PDD → UAT → Rollout • Portfolio oversight with PMO: prioritization, capacity, governance, value realization • Delivery fundamentals: planning, RAID, change control in Agile/hybrid environments • Lean-trained BA; process modeling (BPMN/Visio); benefits modeling; data-driven decisions • Tooling: VIA/ServiceNow, Smartsheet, JIRA, PSA, SharePoint; Power BI • Technical fluency: Power Automate/RPA, Alteryx, Python, SQL, OCR, GenAI/agentic tools • Practical AI business analysis capability, including GenAI use-case discovery, prompt engineering, RAG and knowledge-grounding concepts, AI agent workflows, human-in-the-loop design, AI output evaluation, and responsible AI considerations. Preferred Qualifications • Experience in Automation processes or teams, Shared Services, Operational Excellence, or consulting environment; multi-region delivery. • Finance or Life sciences or healthcare industry exposure. • Automation Anywhere, SAP, PSFT, Azure/Databricks, and enterprise integration (API/GUI) experience. • ITIL, data security, and governance awareness. • Proven executive stakeholder management and executive-ready communications. • Experience defining business and functional requirements for GenAI or agentic AI solutions using platforms or frameworks such as Microsoft Copilot, Azure AI, Cursor, LangGraph, or equivalent enterprise AI technologies. • Understanding of AI solution risks and controls, including hallucination, bias, data privacy, prompt injection, secure grounding, explainability, human oversight, and model or agent performance monitoring Preferred Certifications • Lean Six Sigma