TechDigital Group
Business Analyst – Credit Cards (AMCB)
TechDigital Group, Cherry Hill, New Jersey, United States
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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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.
#J-18808-Ljbffr