Cards Analytics Specialist
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Key skills for this role
About the Role
The role involves portfolio performance reporting, campaign effectiveness analysis, and data-driven decision support using SQL, Excel, and data visualization tools.
Key Skills for This Role
Responsibilities
- Build, maintain, and deliver recurring and ad hoc performance dashboards covering acquisition, activation, spend, ENR, delinquency, attrition, and profitability metrics across the card portfolio
- Conduct deep dive analyses on portfolio segments to identify performance drivers, risks, and growth opportunities
- Design and execute pre/post campaign analytics including control group methodology, ROI calculation, and response rate analysis
- Provide structured analytical support to Cards Product, Portfolio, Marketing, and Risk teams through insight packs, business cases, and scenario analyses
- Identify opportunities to improve data integrity, automate recurring reports, and enhance self serve analytics capabilities
Requirements
- 7 years in cards analytics, portfolio analytics, or business intelligence within banking, payments, or financial services
- Proficiency in SQL and Excel
- Demonstrated experience in cards portfolio analytics (credit and/or debit) within banking or payments
- Experience with at least one data visualisation tool (Tableau, Power BI, or equivalent)
- Professional proficiency in English
- Immediately available or within 30 day notice
Full Job Posting
Purpose of the Project
- The Cards Product and Portfolio teams require dedicated analytical capacity to strengthen data driven decision making across the card lifecycle.
- This role exists to embed a specialist analytics resource who will own the production and interpretation of portfolio performance reporting, diagnose emerging trends and risks, measure campaign effectiveness, and translate data into actionable recommendations for senior stakeholders.
Core Responsibilities and Accountabilities
- Portfolio performance reporting & monitoring (~35%) Build, maintain, and deliver recurring and ad hoc performance dashboards covering acquisition, activation, spend, ENR, delinquency, attrition, and profitability metrics across the card portfolio.
- Portfolio diagnostics & segmentation analysis (~25%) Conduct deep dive analyses on portfolio segments (by product, channel, customer cohort, vintage) to identify performance drivers, risks, and growth opportunities.
- Campaign measurement & effectiveness analysis (~20%) Design and execute pre/post campaign analytics including control group methodology, ROI calculation, and response rate analysis to measure and optimise marketing and engagement campaigns.
- Data driven decision support (~15%) Provide structured analytical support to Cards Product, Portfolio, Marketing, and Risk teams through insight packs, business cases, and scenario analyses that inform strategic and tactical decisions.
- Data quality & automation (~5%) Identify opportunities to improve data integrity, automate recurring reports, and enhance self serve analytics capabilities for business users.
Knowledge and Experience
- 7 years in a cards analytics, portfolio analytics, or business intelligence role within banking, payments, or fintech.
- Exposure to retail banking, consumer lending, or credit risk analytics preferred.
- Cards portfolio management concepts: acquisition funnels, activation rates, spend behaviour, ENR/balance build, attrition, delinquency, and profitability drivers.
- Understanding of card P&L structure (interchange income, fee income, cost of funds, scheme fees, provision/write off).
- Campaign lifecycle analytics: targeting, segmentation, control group design, uplift measurement, and ROI.
- Familiarity with card scheme reporting (performance dashboards and benchmarking tools) preferred.
- SQL proficient in writing complex queries for large datasets (mandatory).
- Excel advanced (pivot tables, VLOOKUP/INDEX MATCH, data modelling, macros) (mandatory).
- Tableau and/or Power BI dashboard design and interactive reporting (mandatory).
- Python or R for statistical analysis, data manipulation, and automation preferred.
- SAS portfolio analytics and data extraction preferred.
- CRM and campaign management platforms (e.g., Salesforce Marketing Cloud, Adobe Campaign, SAS CI) preferred.
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