Card Portfolio Analyst

Data is the heartbeat of our business. We need a hands on analyst who can transform billions of transaction rows into activation playbooks, profit levers, and fraud crushing insights. You'll be the bridge between raw transaction logs and real world decisions, working shoulder to shoulder with Business, Product, Growth, Risk, and Finance. If turning noisy data into clear human actions is your idea of fun, keep reading.

• Combine processor, ledger, and engagement data in BigQuery or Snowflake
• Maintain reproducible SQL/Python jobs that refresh daily
• Publish core dashboards in Power BI or Grafana
• Automate a 10 slide board deck that ships on day 2 of every month

• Define and conduct segmentation analysis on spending behavior and life cycle stage
• Flag dormant or low engagement cards and supply re activation lists to CRM
• Slicing CAC/LTV by cohort; re allocate spending toward high retention channels
• Develop cost benefit analyses on new product/feature recommendations or changes
• Build volume forecasts and elasticity models that help us secure better network terms
• Provide Finance with scenario tables before every partner renegotiation
• Highlight cost variances or fee leakages as they occur

• Quantify the impact of campaigns, rewards, limit changes, and partner offers
• Identify merchant category and time of month triggers that correlate with higher usage
• Advise Business Development on reward partners that fit observed spend patterns

• Map false positive hotspots, tune rules, partner with ML team on new features
• Drive 25 bps annual reduction in fraud losses without hurting approval rates

• 3-6 yrs in card issuing, payments, lending, or top tier analytics role
• Experience with a modern BI tool (Looker, Power BI, Mode, etc.)
• Comfort with statistical testing, cohort and survival analysis
• Storytelling skills-turn noise into narratives executives act on
• Bias for delivering an initial solution quickly and iterating
• Bonus points for experience with fraud decision engines, interchange tables, or basic ML deployment-but curiosity beats checkboxes every time

• Familiarity with interchange regulations and scheme fee tables
• Exposure to fraud rule tuning or decision engine data
• Startup or scale up DNA

• Increase in active card rate
• Fraud and fee drag reduction
• Executive and commercial teams rely on the new dashboards as their primary source of portfolio data
• Number of insight driven product launches / adaptations
• Reduction in management and board reporting time