Transactional Banking Data Analyst

Key Responsibilities:

1. Business Analytics & Use Cases:

· Identify and prioritise Transaction Banking analytics use cases across client behaviour, transactions, revenue, liquidity, onboarding, product usage, cross-sell, and operational efficiency.

· Partner with Business and Product teams to define business problems, KPIs, success measures, and practical analytical solutions.

· Support analytics/AI pilots with a focus on business value, usability, and scalability.

2. Data Analysis & Insights:

· Analyse TB data to identify trends, drivers, risks, opportunities, and performance gaps.

· Translate findings into actionable insights supporting business decisions, product strategy, and operational improvements.

· Validate analytical outputs and ensure they align with business realities.

3. Reporting & Dashboards:

· Develop management reports, dashboards, KPIs, trend analysis, and risk/exception indicators for TB Business and Operations.

· Use AI to automate insight generation, identify exceptions, and simplify analysis of complex datasets.

· Ensure insights are transparent, interpretable, and used as decision-support tools.

4. Data Business Analysis & Requirements:

· Gather and translate business, reporting, KPI, and data requirements for Transaction Banking.

· Contribute to the TB Datamart by defining consistent, reusable metrics and datasets.

· Work with Product, Data, Technology, and AI teams to ensure solutions are practical and aligned with business needs.

5. Data Quality & Governance:

· Perform data quality, validation, and reconciliation checks to ensure reliable reporting and analytics.

· Support metric definitions, data dictionaries, and business rules.

· Drive stakeholder adoption by communicating insights in clear, non-technical language.

older communication, and prioritisation skills