Wise is a global technology company, building the best way to move and manage the world’s money.
Min fees. Max ease. Full speed.

Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.

As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.

More about our mission and what we offer.

The team you will join: Fraud Risk team

The team is dedicated to safeguarding our platform against financial crime and ensuring the protection of our legitimate customers. Leveraging cutting-edge machine learning, real-time transaction monitoring, and data analysis, our team is responsible for developing and enhancing payment fraud detection systems. Software engineers, data analysts, and data scientists collaborate on a daily basis to continuously improve our systems and provide support to our fraud investigation team.

Our vision is:

• Build a globally scalable payment fraud prevention and detection real-time engine to keep Wise as a secure environment for our legitimate customers.
• Utilise machine learning techniques to identify potential risks associated with customer activity.
• Foster a strong partnership between our fraud investigators and the product team to develop solutions that leverage the expertise of fraud prevention specialists.
• Not only meet the requirements set by regulators and auditors but also surpass their expectations.

What does it take?  

• 6+ years of experience working with Java, Spring framework, asynchronous message queues and have worked with microservices architecture – this is essential 
• Experience with CI/CD pipelines and Distributed and Concurrent Systems
• Hands-on experience with Kafka, Kafka Streams or Apache Flink
• Experience with OLAP databases or data-lakes with Kafka ingestion is a plus
• A strong product mindset and passion for user experience, you prioritise work with the customers in mind and make data-driven decisions to fix customer pain-points
• You believe in and follow best coding practices, code reviews and open feedback
• Being able to work autonomously on customer problems is a key to success - you take responsibility and end-to-end ownership of your projects: drive and own them to make sure we hit the goals we want to achieve
• Great communication skills (both verbal and written) and the ability to articulate complex, technical concepts to non-technical audience
• Hands-on experience working with relational and non-relational databases, query optimisations, designing and evolving schemas
• Experience with machine learning basics (data pipelines, feature engineering, recall/precision, familiarity with machine learning systems in production) is a huge plus

What does success look like?

• You'll be having a real world impact by building financial crime prevention systems which protect customers from falling victims of fraud or scams
• You’ll have onboarded and found your place through understanding your team and tribe vision and how you can contribute
• You'll closely collaborate with product managers, data scientists, data analysts, engineers and other product teams on a daily basis.
• You’ll understand the reasons behind problematic payments and customer difficulties and how to go about solving them
• You’ll be raising the automation level to enable scaling of the product
• Understand our customers and the impact our product makes in their lives 

For everyone, everywhere. We're people building money without borders  — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.

We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.

If you want to find out more about what it's like to work at Wise visit Wise.Jobs.

Keep up to date with life at Wise by following us on LinkedIn and Instagram.