We’re looking for a Middle+ Data Analyst to work on the heart of the credit cards profitability engine - to build and maintain our end-to-end NPV / unit economics model. The role goes beyond reporting - you will help the Head of Economics implement model logic in Python/SQL, automate data flows, validate outputs against real portfolio performance, and deliver decision-ready results. Each task is evaluated through the lens of business value. Key responsibilities Implement and maintain NPV / unit economics models in Python + SQL (clean, testable, versioned logic) Build reliable datasets required for economics (cohorts, cashflows, losses, funding, fees, revenue streams) with help of other analysts Automate scenario runs and sensitivity analysis (pricing, limits, product changes) Validate model outputs vs actual portfolio performance and investigate gaps Translate model logic into implementation-ready specs when needed Step in beyond your scope when needed — we value ownership over rigid roles Requirements and expectations 2-3+ years of hands-on experience in data analytics Proficiency in Python (pandas) and SQL for data exploration and analytics implementation Solid understanding of unit economics / financial modeling concepts (cashflows, NPV, cohorts) High attention to detail — small errors break economics in production Knowledge of unit economics is required (including deep understanding of the concept, experience in modeling, or at least working with such models). Direct experience in unit economics modeling for credit products is a strong plus.