Director of Data Science – Engineering, Fraud Platform

🕒 September 24

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

📊 Data Scientist

👻 Ghost score 24%

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Zepz

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2021

💳 Fintech

👥 B2C

💰 $165M Debt Financing - Zepz on 2025-03

Fintech • B2C

Zepz is a fintech company that operates digital remittance brands (notably WorldRemit and Sendwave) offering fast, secure, mobile-first cross-border money transfer services for consumers. The company emphasizes fair, fast and flexible payments, a world-class customer experience, and global reach — enabling app-based transfers to over 130 countries, with reported volumes of about $10 billion transferred and 50 million customer transactions in 2020 across more than 5,000 corridors. Zepz positions itself as customer-focused and growth-oriented, with hundreds of employees and multiple international offices supporting consumer remittances primarily to regions such as Africa and Asia.

📋 Description

• 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

🎯 Requirements

• Track record of leading a data organization of comparable size (roughly 15–25 people) • Experience supporting the professional development of managers and senior-level individual contributors • Track record leading mixed technical teams of Data Scientists, Machine Learning Engineers, and Analytics Engineers • Demonstrable ownership of data quality at scale, including contracts, observability, lineage, and semantic consistency • Fluency with modern lakehouse and analytics engineering practices, including Databricks or equivalent, dbt-style transformation, feature stores, real-time feature serving, and datasets as products with owners and SLAs • Experience with production ML in a real-time context, including model monitoring, drift detection, and retraining pipelines • Proven experience with AWS at scale • Direct experience leading FinCrime/Fraud or Identity engineering or data science teams • Ability to achieve outcomes from teams that do not report to you • At least 8+ years of technical experience in a hybrid IC/management role • Ability to attract and retain top talent and lead teams with diverse skill sets • Experience working with Engineering and Product leaders • Exceptional judgment and ability to make effective tradeoffs while scaling quickly • Prior experience leading FinCrime/Fraud or Identity teams, including knowledge of card fraud, ATO, first-party fraud, synthetic identity, money mule networks, regulatory context, and customer-experience tradeoffs • Understanding of identity verification, KYC, and onboarding data as a data domain • Experience partnering with Risk, Compliance, and Legal on regulatory obligations • AI literacy, including automation, AI application, prompt effectiveness, critical evaluation of AI output, and responsible AI use • Practical professional experience using AI tools • Experience with Claude is nice-to-have, not essential • Bonus: scaling startup experience, data mesh or domain-oriented data ownership, stablecoins and cryptocurrencies, production AI, k8s, gRPC, Spring Boot, Java, or Python

🏖️ Benefits

• Unlimited annual leave • Great healthcare benefits • Employee discounts • Flexible working environment • Remote work tools • Team off-sites and connects • Professional development and support to excel

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