[Hiring] Director of Data Science & Engineering, Fraud Platform @Zepz

Role Description

This is a high-visibility, high-accountability role — outcomes are reported to C-level and the board, and the role owns both the data strategy and the model performance behind systems that directly protect revenue and customer trust. The mandate in one line: own what data is generated and how it is generated and consumed across the Identity and Financial Crime domains. Almost every consequential decision Zepz makes about a transaction — is this person who they say they are, is this payment safe, is this account compromised — is a decision made on data. Identity is our single largest producer of that data. Financial Crime is our single largest consumer of it. Both sit in the same engineering organization, and today no one owns the path between them. The result is a permanent tax on everything downstream: problems discovered late, by the people least able to fix them at source. This role exists to remove that tax. You will lead a team of 25+ Data Scientists, Machine Learning Engineers and Analytics Engineers across the Identity and Financial Crime domains.

What you will own

• Own the definition, generation, quality and consumption of data across the Identity and Financial Crime domains — what gets produced, what it means, what guarantees come with it, and who is accountable when those guarantees are not met.
• Make data quality an engineering discipline rather than a downstream cleanup exercise: producer/consumer contracts, freshness and integrity monitoring, lineage, a named owner for every critical dataset, and a real path from a detected anomaly to a fix at source.
• Own the models and analytics behind how Zepz detects fraud and financial crime — feature engineering, model development, deployment, monitoring and retraining.
• Lead a mixed organization of Data Scientists, Machine Learning Engineers and Analytics Engineers.
• Partner as a peer with the Engineering Manager who owns the fraud detection platform.
• Partner with our central data function, which owns core data infrastructure and platform tooling.
• Set standards with Identity engineering teams who do not report to you.
• Create high-performing teams with a bias toward shipping without sacrificing reliability or trust in the numbers.
• Hire, retain, and level up superlative talent to ensure our team remains world-class.
• Roll up your sleeves when models degrade or data breaks.

In your first few months, you will

• Establish an honest, evidenced baseline of data quality across the identity-to-financial-crime path.
• Agree a written ownership model with the central data team and the Identity engineering leads.
• Instrument the critical path, so data issues are detected by monitoring.
• Get to know the models — how they perform, how they degrade, how retraining actually works today.
• Assess the team: identify the gaps, the flight risks and the people ready for more.
• Promote a culture of ownership, accountability, and shipping.

What you bring to the table

• You have a track record of leading a data organization of comparable size (roughly 15–25 people).
• Track record of leading mixed technical teams — Data Scientists, ML Engineers, Analytics Engineers.
• Demonstrable ownership of data quality at scale.
• Fluency with modern lakehouse and analytics engineering practice.
• Experience with production ML in a real-time context.
• Proven experience with AWS at scale.
• Direct experience leading FinCrime/Fraud or Identity engineering or data science teams.
• The ability to get outcomes from teams that don't report to you.
• At least 8+ years of technical experience in a hybrid IC/management role.
• You can attract and retain top talent and lead teams with diverse skill sets.
• You work well with Engineering and Product leaders.
• You have exceptional judgment.

FinCrime & Identity Domain

• Bring prior experience leading FinCrime/Fraud or Identity teams.
• Understand identity verification, KYC and onboarding data as a data domain.
• Partner with Risk, Compliance, and Legal on regulatory obligations.
• Own incident response leadership when major fraud events occur.

Bonus points

• Have worked at a scaling startup previously.
• Have experience with data mesh or domain-oriented data ownership models.
• Have experience working with stablecoin and cryptocurrencies.
• Have experience working with AI in a production environment.
• Have worked in environments with k8s / gRPC / Spring Boot / Java / Python.

AI Literacy & Tools

• Proficient depth of knowledge around automation, AI and how those can be applied in your area of work.
• Practical experience using AI tools in a professional context.
• Strong AI literacy.
• Awareness of the ethical considerations and responsible use of AI in the workplace.
• Prior experience using Claude (Anthropic) is a nice-to-have.

Ready to Apply?

If you want to join us in our journey to help break barriers in financial access and improve lives globally, there's no better place or time to join.