Business Analyst – Corporate Banking (AI/ML & Advanced Analytics)
Location: Abu Dhabi, UAE (Onsite)
Experience: 7–10 Years
Job Summary
BigTapp is looking for an experienced Business Analyst – Corporate Banking to support AI/ML-driven digital transformation initiatives for a leading banking client in Abu Dhabi.
The ideal candidate will have strong experience working with Corporate / Wholesale Banking business teams, particularly in Customer Experience, Revenue Growth, Sales Analytics, Relationship Management, Profitability Analytics, and Digital Banking initiatives.
The Business Analyst will collaborate closely with senior banking stakeholders, Relationship Managers, Product Owners, Data Engineers, and Data Scientists to identify business opportunities, define AI/ML use cases, and convert business requirements into functional specifications and analytical solutions.
The role requires an individual who can bridge business and technology while driving measurable business value through analytics and AI.
Mandatory Banking Domain Experience
Candidates must have hands-on experience in Corporate / Wholesale Banking, with strong exposure to customer-facing and revenue-generating functions.
Priority Domain Areas
Customer Experience
- Digital Banking
- Customer Journey
- Customer Engagement
- Customer Analytics
- Digital Onboarding
- Relationship Manager Enablement
- KYC / Customer Lifecycle
Revenue & Sales
- Relationship Management
- Cross Sell
- Upsell
- Lead Generation
- Customer Segmentation
- Sales Performance Analytics
- Campaign Analytics
- Revenue Optimization
- Next Best Offer / Next Best Action
Profitability
- Client Profitability
- Portfolio Profitability
- Customer Lifetime Value (CLV)
- Net Interest Margin (NIM)
- Revenue Analytics
- Cost to Income
- Banking KPIs
- Business Performance Dashboards
Good to Have
Exposure to one or more of:
- Credit Risk
- Corporate Lending
- Trade Finance
- Treasury
- Basel
- RWA
- Fraud Analytics
Note: Candidates with only Risk experience and no Customer, Revenue, or Profitability exposure will not be considered.
AI / ML Exposure
Candidate should understand AI/ML business applications and have participated in defining analytical business use cases such as:
- Customer Churn Prediction
- Revenue Forecasting
- Client Segmentation
- Next Best Action
- Relationship Manager Recommendations
- Cross Sell / Upsell Models
- Client Profitability Models
- Customer Behaviour Analytics
- Fraud Detection
- Credit Risk Models (Good to Have)
The expectation is business-side ownership of AI/ML initiatives rather than model development.
Key Responsibilities
- Engage with Corporate Banking stakeholders to identify business challenges and improvement opportunities.
- Gather, analyse and document business requirements.
- Conduct stakeholder workshops and discovery sessions.
- Translate business problems into AI/ML and Analytics use cases.
- Prepare:
- BRD
- FSD
- User Stories
- Use Case Documents
- Process Flows
- Functional Specifications
- Work closely with Data Engineers and Data Scientists to define data requirements and business logic.
- Support solution design, UAT, Go-Live and Hypercare.
- Present analytical findings and business recommendations to senior management.
- Monitor adoption and business value delivered through AI-driven solutions.
Business Analysis Skills
Mandatory experience in:
- Requirement Gathering
- Stakeholder Workshops
- BRD
- FSD
- User Stories
- Process Mapping
- Gap Analysis
- Functional Specifications
- UAT
- Agile Delivery
- Product Backlog Grooming
- Sprint Planning
Banking Analytics Experience
Strong understanding of:
- Banking KPIs
- Customer Analytics
- Sales Analytics
- Portfolio Analytics
- Profitability Analytics
- Campaign Analytics
- Relationship Manager Dashboards
- Executive MIS Reporting
Technical Exposure
Good understanding of:
- Banking Data
- Data Warehousing
- Data Lakes
- SQL (preferred)
- Power BI / Tableau / Qlik (preferred)
- Azure DevOps / Jira
- AI/ML lifecycle
- Data Science collaboration
Hands-on model development is not required.
Stakeholder Management
Candidate should have experience interacting with:
- Corporate Banking Business Heads
- Relationship Managers
- Sales Teams
- Product Owners
- Technology Teams
- Data Engineering Teams
- Data Science Teams
- Senior Business Leadership
Preferred Industry Experience
- UAE Banking
- GCC Banking
- Wholesale Banking
- Corporate Banking
- Commercial Banking
Experience working with UAE/GCC banks will be highly preferred.
Certifications
Preferred
- CBAP
- Scrum
- Agile
- AI Fundamentals
- Banking Certifications
Success Criteria (KRA)
- High-quality Business Requirement Documents
- Well-defined AI/ML business use cases
- Strong stakeholder engagement
- Successful UAT completion
- Business adoption of AI-driven solutions
- Measurable improvement in customer experience, sales effectiveness, and profitability
KPI
- Requirement quality
- Stakeholder satisfaction
- Business adoption
- AI use case success
- Revenue impact
- Customer engagement improvement
- Reduction in requirement gaps
- Delivery quality
