Business Analyst

June 9, 2026
Application ends: September 7, 2026

Job Description

REQUIREMENTS

  • Strong Corporate Banking domain expertise.
  • 7–10 years of experience in Corporate Banking Business Analysis.
  • Strong understanding of Corporate Lending, Trade Finance, Cash Management, Treasury, Risk Management, Relationship Management.
  • Knowledge of banking metrics like NIM, RWA, CLV.
  • Familiarity with core banking systems, credit workflows, and banking data structures.
  • Experience in UAE / GCC banking landscape is highly preferred.
  • Strong experience in requirements gathering, stakeholder management, BRD/FSD preparation.
  • Understanding of AI/ML concepts, including Supervised / Unsupervised Learning, Data Labeling, Model Accuracy Metrics.
  • Ability to collaborate with Data Engineers / Data Scientists.
  • Experience in AI/ML or digital transformation initiatives in banking.
  • Excellent communication and presentation skills.
  • Strong stakeholder management abilities.
  • Ability to manage cross-functional teams in a consulting environment.
  • Bachelor’s / Master’s degree in Finance, Business, Economics, or related field.
  • Certifications like CBAP or AI/Data certifications are a plus.
  • Prior consulting experience in banking transformation or AI initiatives.

RESPONSIBILITIES

  • Engage with senior stakeholders across Corporate & Institutional Banking to identify AI/ML opportunities.
  • Conduct workshops and gather business requirements across domains such as Trade Finance, Cash Management, Lending, Treasury, and Risk.
  • Translate business problems into detailed AI/ML use cases like:
    • Churn Prediction
    • Next Best Action
    • Credit Risk Scoring
    • Revenue Forecasting
    • Fraud Detection
  • Prepare Business Requirement Documents (BRDs), Functional Specifications, and Use Case Blueprints.
  • Define data requirements, KPIs, business rules, and success metrics for AI models.
  • Act as the liaison between banking stakeholders, data engineers, and data scientists.
  • Support UAT, validation, and model adoption across business functions.
  • Monitor post-deployment model performance and recommend improvements.
  • Present business insights and AI use case recommendations to senior management.

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