Cards Data Analyst Intern

About the Role

The Cards Data Analyst intern will focus on analyzing card transaction data, developing insights, and supporting data-driven decision making for our cards business portfolio.

What You Will Do

• Analyze card transaction data, customer spending patterns, and performance metrics to identify trends, anomalies, and business opportunities


• Create regular reports and dashboards for stakeholders, including management reports on card portfolio performance, customer segmentation analysis, and risk indicators


• Develop compelling visualizations and presentations to communicate complex data insights to both technical and non-technical stakeholders


• Maintain data quality standards, perform data validation, and ensure accuracy of analytical outputs using SQL and other data tools


• Support the creation of KPIs and metrics for card products, assist in A/B testing analysis, and provide insights for product optimization


• Work closely with business, product, and engineering teams to understand business requirements, provide analytical support for decision-making, and contribute to cross-functional projects

What We Are Looking For

• Diploma holder / Degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or related analytical discipline


• Experience with data analysis tools and programming languages (Python, R, SQL) will be a plus


• Knowledge of financial services or payments industry is preferred but not required


• Strong analytical and quantitative skills with attention to detail and accuracy in data handling


• Excellent communication skills with ability to present complex data insights in a clear and actionable manner


• Strong problem-solving abilities with a curious mindset and ability to think critically about data


• Self-motivated with strong organizational skills and ability to manage multiple analytical projects simultaneously


• Proficiency in data visualization tools (Tableau, Power BI, or similar) and Excel is a plus


• Familiarity with statistical analysis and machine learning concepts is preferred