Cash Data Analyst

The Cash Product Data Analyst is responsible for the data analytics pertaining to the working capital management solutions related to Cash Management. This is established through usage of data automation and analytics tools, along with engagement with multiple internal stakeholders.

Strategy and Planning

• Identify and address areas to improve efficiency and increase automation of datasets and reporting, pertaining to Cash Management products and solutions, in order to reduce turnaround time and enable more informed decision-making.
• Support a digital vision for the enterprise and identify opportunities for differentiating digital capabilities and solutions in the area of data analytics and MIS reporting.
• Assist in analyzing data and performing market analysis to identify potential opportunities and justify requirements to drive the success of partnerships.

Business Performance and Management

• Responsible for the end-to-end management and preparation of regular and ad-hoc data analytics reports and management presentation decks, on a timely basis to communicate the financial and non-financial progress/status of Cash Management products to internal and external parties.
• Track and analyze data of Cash Management products to identify potential opportunities and justify requirements that will increase product utilization. This includes breaking down the P&L and business drivers to produce clear insights, historical tracking, and forecasting purposes.
• Work closely with all stakeholders to develop in-depth data analytics and performance reports on an ongoing basis for all Cash Management products and solutions, in order to develop appropriate strategies/campaigns to drive product usage and profitability.
• Enhance and maintain Cash Management client-level profitability reporting to facilitate tracking and fulfillment of clients' earnings.
• Prepare and process campaign-related rewards/rebates/interest for clients.
• Perform market/competitive analysis on data results where required.
• Utilize appropriate automation/AI tools to perform business data analysis in a streamlined and accurate manner.

Stakeholder Collaboration

• Constant communication and engagement of internal stakeholders on data analytics requirements and output.

Regulatory Compliance

• Practice standards and role model behaviors that demonstrate the core values of the bank, particularly in areas of data classification, data labeling, and data retention.

Additional Tasks

• Assist in ad-hoc data extraction where required for analysis purposes, e.g., repricing.