Lead Product Manager, Veriff Network
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About Veriff Veriff is building trust infrastructure for the internet. Our AI-powered identity verification and fraud prevention platform helps businesses across fintech, crypto, gaming, mobility and marketplaces know who their users are, and whether they can be trusted, in 230+ countries and territories. We build our own technology end to end, and every verification we run teaches us something about how fraud really works.
The role Veriff sees fraud at a scale and breadth that no single platform can see on its own. Our job now is to turn that advantage into products customers can see, measure and act on, and to build the network that makes it compound.
As Lead Product Manager for Fraud on the Veriff Network team, you will make the fraud detection, prevention and accuracy strengths of our product legible to customers. You will own the concrete product experiences that do this, such as a Feedback API that lets customers tell us what happened after a decision, fraud insights inside Station (our customer portal), and automated fraud reporting. You will also lead the customer engagement that turns those experiences into a feedback loop: customers share outcomes and signals, our detection gets sharper, and every platform on the network benefits.
This is one of the first roles on the Veriff Network, and it directly shapes how we package, sell and grow our fraud offering.
What success looks like In your first 90 days, you will have assessed our fraud product roadmap and packaging and agreed a revised version with product and fraud leadership. You will have identified the top three to five fraud product improvements, with the highest-priority items shaped and in development.
By six months, the first updated fraud product offering is live with a group of design and beta partners.
By nine to twelve months, a shared-signal pilot is running with a set of platforms, as the first step toward a cross-platform fraud network.
By twelve months, the improved fraud products are generally available and are measurably helping us attract and close deals with our core customer segments.
What you'll bring
- Fraud and risk expertise. You have shipped fraud or risk products, or you have been responsible for fighting fraud and managing risk at a scaled, digital-native company. You understand attack patterns, how fraud teams actually work day to day, and how the precision/recall trade-off plays out in the real world.
- Network product experience. You have worked on network-effect or marketplace data products, where aligning incentives between participants and building feedback loops are central to the product.
- Data and ML product craft. You can specify a signal, read a model evaluation, and ship and manage a rules engine. You know what to build yourself and what to leave to data science.
- Customer discovery with fraud teams. You can get fraud and trust leaders at platforms talking openly, and you turn what you learn into a clear roadmap.
Nice to have
- Experience building with operations teams. Our fraud operations experts are the source of truth on what fraud looks like in practice, and the right person turns their judgment into product. If you haven't worked closely with an operations team before, you'll need to show strong cross-functional collaboration skills.
- Commercial packaging. You have shaped how a product is priced and sold, and worked deals alongside Sales.
Why Veriff?
We are the preferred identity verification platform partner for the world’s most innovative growth-driven organizations helping conveniently verify and safeguard users anywhere in the world. We support the broadest number of identity documents from nearly every country and territory in the world - and this is continually increasing! With a diverse team in the United States, United Kingdom, Spain, and Estonia, as well as robust backing and funding from investors including Accel, Alkeon, IVP, Tiger Capital, and Y Combinator,...
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About Veriff
Learn more about Veriff and their company culture.
Identity verification platform using machine learning for facial verification, liveness detection and identity decisions.
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