Why the Right Hire Matters More in Fintech
Payments is changing fast. Modernisation, tighter regulation and the rise of machine learning are reshaping fraud, identity, decisioning and customer experience at the same time, and the companies building in this space are moving faster than their hiring can keep up with.
In this environment, a wrong hire does not just slow things down. It creates risk. A delayed platform release, a fraud model that misses what it should catch, a security gap in a system that moves real money. The cost of getting it wrong here is measurable, and often expensive.
We recruit the data, machine learning, engineering and technical leadership talent these businesses run on. We know financial services from the inside, which means we understand the regulation, the risk and the difference between a demo and a system that holds up when it is moving real funds.
Our Focus
We are deliberately narrow. Two areas, and the data and engineering talent that builds them.
Payments Fraud, Risk and Identity
The data and machine learning layer of payments: the people who build fraud models, decisioning systems and identity-verification technology. This is where payments meets applied machine learning, and the talent is scarce because the work has to be fast, accurate and resilient against people actively trying to beat it.
Roles we place: machine learning engineers and data scientists building fraud and risk models; decisioning and transaction-monitoring engineers; identity and verification engineers; and data engineers feeding the platforms beneath them.
Embedded and Open Banking Payments
The companies building pay-by-bank, embedded payments and open-banking platforms. This is the fastest-growing end of payments, and where most of the firms in our size range sit. The work is data, API and platform-heavy.
Roles we place: backend and platform engineers building high-volume, low-latency systems; API and integration engineers; data engineers; and product people who understand the payments journey.
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