Teams at Eneba

Own fraud detection and prevention for a product by analyzing large datasets, identifying fraud patterns, creating risk rules, optimizing false-positive rates and 3DS decisions, and improving verification workflows. Collaborate with Product, Payments, Data, and Engineering teams while tracking fraud trends and communicating data-driven recommendations. Strong SQL and practical payments-risk expertise are required; Python and fintech experience are preferred.

Build and maintain data pipelines, infrastructure, data models, and automation for analytics and machine learning workflows. Collaborate with ML engineers on model training, quality assessment, and releases. Improve internal data delivery processes and enable efficient access to large-scale organizational data.

Analyze payment funnel health across multiple providers by monitoring alerts, authorization rates, decline codes, and conversion. Lead root-cause investigations into technical defects, user behavior, and processor outages; translate findings into actionable insights for cross-functional stakeholders. Build reporting and dashboards, partner with Product, Engineering, Data Science, and Fraud, and develop expertise in payment funnel performance.