Zepz

Data Scientist

• Own the definition, generation, quality, and consumption of data across Identity and Financial Crime domains
• Establish producer/consumer contracts, freshness and integrity monitoring, lineage, dataset ownership, and source-level remediation
• Own fraud and financial-crime detection models and analytics, including feature engineering, development, deployment, monitoring, and retraining
• Lead a mixed organization of 25+ Data Scientists, Machine Learning Engineers, and Analytics Engineers
• Partner with the Engineering Manager responsible for the fraud detection platform
• Collaborate with the central data function on infrastructure and platform tooling
• Set data standards with Identity engineering teams through influence and evidence
• Build high-performing teams while balancing delivery, reliability, and data trust
• Hire, retain, and develop world-class talent
• Review technical work and help execute strategy when models degrade or data breaks
• Establish a measured baseline of data quality across the identity-to-financial-crime path
• Agree ownership models and dataset contracts with central data and Identity engineering leads
• Instrument critical data paths for proactive monitoring
• Assess model performance, degradation, retraining, and concentrated risk
• Assess team capability, flight risks, and hiring needs
• Promote ownership, accountability, and shipping
• Lead incident response for major fraud events, model failures, or data-integrity failures
• Report outcomes to C-level executives and the board

Director of Data Science – Engineering, Fraud Platform