Business Analysis Manager

Transform Consumer and Community Banking (CCB) Operations oversight with AI-enabled, full-population controls testing and audit-ready evidence. You'll own end-to-end analytics and Large Language Model (LLM) enabled automation for exception triage and reporting, while governing an enterprise knowledge base that stays current, trusted, and regulator-aligned. As a Continuous Monitoring Quality Manager on the Quality team, you will partner closely with CCB Operations business lines (e.g., Collections/Recovery/Auto Operations) to design, develop, and implement AI-enabled continuous monitoring and full-population quality testing frameworks that strengthen the control environment, improve audit readiness, and drive operational excellence at scale. You will own end-to-end delivery of data analytics solutions, test population isolation, test design, controls reporting, and LLM-enabled automation (including prompt engineering, workflow integration, and governance). You will also serve as a strategic owner for an enterprise knowledge base, ensuring standards, content governance, and alignment with operational and regulatory expectations. Job responsibilities Deliver AI-enabled full-population monitoring, shifting oversight from sampling-based review to automated controls testing and scalable evidence capture. Design and implement end-to-end continuous monitoring tests by isolating test populations, defining business rules/thresholds, implementing automated validation and reconciliation checks, partnering with operations, compliance, risk, and control stakeholders to ensure coverage and intent alignment. Drive prompt engineering and LLM workflow delivery to accelerate knowledge base curation and standardization, controls reporting narratives and executive summaries (grounded in approved sources), intelligent triage/routing of exceptions (with human-in-the-loop controls where required). Establish LLM/prompt governance practices including versioning, performance testing, outcome validation, documentation, and controlled change management suitable for a regulated environment. Own the enterprise knowledge base strategy, including taxonomy/metadata standards, content lifecycle (create/review/retire), and quality controls to ensure content remains current, trusted, and auditable. Proactively analyze data to identify themes, trends, and performance opportunities; translate insights into prioritized improvements and automation roadmap items. Prepare and deliver management reporting on test results, key performance metrics, emerging risks, and remediation plans—clearly communicating impacts and actions. Demonstrate urgency responding to escalations, adverse performance indicators, and shifting priorities to maintain program effectiveness. Handle highly confidential information with professionalism and integrity, adhering to JP Morgan Chase privacy and security standards. Required qualifications, skills, and capabilities Seasoned experience in data analytics/development with a focus on quality testing methodologies, controls testing, or continuous monitoring. Seasoned experience delivering automation at scale (test frameworks, exception management, reporting automation, repeatable controls reporting). Working knowledge of AI-enabled delivery concepts, including prompt engineering (structured outputs, reusable templates, test cases), workflow controls (human-in-the-loop, approvals), validation approaches to ensure accuracy/consistency of automated outputs. Advanced skills in Microsoft Office products (Excel, PowerPoint, Access) for complex analysis and executive-ready communication. Excellent written/verbal communication skills to translate technical findings into clear recommendations for diverse stakeholders. Proven ability to deliver results in high-pressure environments with tight deadlines and shifting priorities. Strong problem-solving and conflict resolution skills. Preferred qualifications, skills, and capabilities Demonstrated experience supporting Collections/Recovery/Auto Operations environments and related datasets. Proven experience with enterprise knowledge management (taxonomy, metadata, governance, content lifecycle). Strong familiarity with AI enablement patterns such as grounding/RAG-style approaches (ensuring outputs align to approved knowledge sources) and evaluation methods to monitor quality over time. Hands-on experience with Webstats and/or ACES. Relevant certification in Six Sigma, Lean, or similar process improvement methodologies. Influential ability to drive change across business, technology, and control stakeholders to embed quality practices.