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Business Analyst – Credit Cards; AMCB

Job in Cherry Hill Township, Cherry Hill, Camden County, New Jersey, 08002, USA
Listing for: TechDigital Group
Full Time position
Listed on 2026-01-17
Job specializations:
  • IT/Tech
    AI Engineer, Data Analyst
Salary/Wage Range or Industry Benchmark: 95000 - 125000 USD Yearly USD 95000.00 125000.00 YEAR
Job Description & How to Apply Below
Position: Business Analyst – Credit Cards (AMCB)
Location: Cherry Hill Township

Role Overview

The Senior Business Analyst will support Client's American Consumer & Commercial Banking (AMCB) AI POD, partnering with Product, Data Science, Engineering, Risk, and Compliance teams to deliver AI and advanced analytics solutions across the U.S. Commercial Banking portfolio.

This role focuses on translating commercial banking business needs, regulatory expectations, and risk controls into clear, compliant, and actionable requirements that enable responsible AI adoption across lending, treasury, servicing, fraud, and operations.

Key Responsibilities Commercial Banking & AI Use-Case Enablement
  • Support AI and advanced analytics initiatives across U.S. Commercial Banking, including:
    • Commercial lending & credit underwriting
    • Client onboarding & KYC
    • Transaction monitoring & fraud detection
    • Portfolio monitoring & early warning indicators
    • Operational efficiency & intelligent automation
  • Partner with Product Owners and AI leads to define use cases, epics, and feature roadmaps for AI-enabled capabilities.
  • Translate complex business problems into data-driven and AI-ready requirements.
AI Governance, Risk & Compliance
  • Embed Responsible AI, model risk, privacy, and regulatory controls into requirements and delivery artifacts.
  • Partner with Risk, Compliance, Legal, and MRM teams to ensure AI solutions meet U.S. regulatory expectations.
  • Support documentation for:
    • Model assumptions and limitations
    • Explainability and transparency requirements
    • Data lineage and data quality controls
    • Human-in-the-loop and override mechanisms
  • Assist with regulatory exam readiness, risk assessments, and audit inquiries related to AI solutions.
Agile POD Delivery
  • Act as the lead Business Analyst within an Agile AI POD (Product Owner, Data Scientists, ML Engineers, Platform teams).
  • Own and author epics, features, user stories, and acceptance criteria for AI and analytics initiatives.
  • Drive backlog refinement, dependency management, and sprint readiness.
  • Facilitate workshops with business, risk, and technical stakeholders to clarify requirements and align on outcomes.
Data & Analytics Requirements
  • Define data requirements including sources, attributes, quality rules, and usage constraints.
  • Collaborate with Data Engineering teams on data pipelines, feature engineering inputs, and integrations.
  • Support validation of AI outputs against business expectations and regulatory requirements.
Tools & Documentation
  • Manage requirements and delivery artifacts in JIRA.
  • Maintain documentation, process flows, decision logs, and AI governance artifacts in Confluence.
  • Contribute to:
    • Business and functional requirements
    • Data mapping and lineage documents
    • Model governance and control documentation
    • UAT and model validation support materials
Required Qualifications
  • 8+ years of Business Analysis experience in banking or financial services.
  • Strong experience supporting Commercial Banking or Corporate Banking domains.
  • Hands‑on experience delivering AI, ML, or advanced analytics initiatives in a regulated environment.
  • Strong understanding of:
    • Commercial lending and servicing processes
    • KYC / AML / fraud controls
    • U.S. banking regulatory expectations
  • Advanced experience working in Agile / POD-based delivery models.
  • Expert‑level experience with JIRA and Confluence.
  • Excellent stakeholder engagement and communication skills.
Nice to Have
  • Experience working with Data Science, ML, or AI platform teams.
  • Exposure to Model Risk Management (MRM) frameworks.
  • Familiarity with Responsible AI principles.
  • Experience supporting regulatory exams involving analytics or models.
  • CBAP, Agile, or analytics‑related certifications.
Success Factors at TD
  • Ability to balance innovation with risk and compliance.
  • Strong collaboration across business, technology, and risk.
  • Comfort working in ambiguity and fast‑moving AI environments.
  • Clear, structured communication with senior stakeholders.
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