Senior Software Engineer - Fraud Risk (relocation support provided)

Company Description

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 life 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.

Job Description

Team you will be joining: Fraud Risk

The Fraud Risk team at Wise 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 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 Main Vision Points Are

Build a scalable and maintainable fraud detection engine where we optimise for speed (<1s risk assessment) and throughput (20k transactions per minute) at the same time

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.

Is that you?

• Software engineering experience, with significant experience in Java or other JVM-based languages.
• Hands-on experience working with relational and non-relational databases, query optimisations, designing and evolving schemas
• Hands-on experience with Kafka, Kafka Streams or Apache Flink
• Experience with OLAP databases or data-lakes (Apache Iceberg) with Kafka ingestion is a plus
• Experience with machine learning basics (data pipelines, feature engineering, recall/precision, familiarity with machine learning systems in production), working with Apache Spark and Amazon SageMaker is a huge plus
• Being able to propose technical solutions that optimise for latency and throughput at the same time - aka: p99 end-to-end latency is under 1 second for real-time payment fraud checks even when a significant amount of transactions are in the system
  
  

What does success look like?

• You’ll have found your place in our mission by understanding how to drive engineering solutions and suggesting future challenges
• You’ll understand our customers and the impact our product makes in their lives
• You’ll make contributions to the wider engineering goals of the company
• You’ll inspire a team environment where ideas are shared and openness is valued
• You’ll help us scale-up and build a world class money product that impacts millions of customers
  
  

Additional Information

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.