BUSINESS ANALYTICS OFFICER

The Credit Card Business Analytics Officer is primarily responsible for the design, development, and deployment of Business Dashboards and other reporting requirements which are used by management to monitor, evaluate, and forecast business volume and profitability performance driving the overall business analytics requirements of Mass Retail Segment, to enable data-driven market, financial, portfolio, and customer behavior analysis for strategy formulation in line with bank’s business growth objectives.

Core Responsibilities

• Develops data-driven insight on acquisition and marketing program under the Segment/Group.
• Leverages internal and external data source to analyze industry and customer trend, highlighting opportunity to improve brand equity, customer growth, and perception
• Understands program and campaign initiative, providing data and analysis for parameter validation or potential enhancement
• Designs, maintains, and enhances Business Dashboard and other Business MIS tool to align with business specification
• Ensures data integrity and delivers timely, accurate production of regular and ad hoc business MIS requested by Unsecured Lending, Cards, and BanKo business team to monitor, evaluate, and forecast business volume and profitability performance
• Supervises the development of business MIS report required by business head and specialist, ensuring proper documentation for consistency in MIS preparation
• Reviews and validates program (e.g., SAS, Excel, Approach, or similar software) created by business MIS analyst to confirm that MIS reporting conforms to the requirement of business owner and specialist
• Initiates enhancement to the MIS framework and implements process improvement to operationalize existing dashboard and deploy tactical report
• Collaborates with Data Management team on data requirement needed to generate MIS and analytical tool
  
  

• Bachelor’s Degree in Statistics, Mathematics, Economics, Data Science, or Engineering
• Experience in Data Management, Data Engineering, Risk Modeling/Data Science, Credit risk management, Collections, Fraud, Data science/analytics or related disciplines in a consumer lending industry
• Proficient in data/analytical tools, e.g., SAS, Python, VBA, Tableau, etc. and any credit, collections or fraud systems
• Analytical and good problem-solving skills
• Excellent written and oral communication skills with distinct ability to convey complex data in a concise understandable manner