Senior Backend Engineer - Fraud Decisioning

The team you will join: Fraud Decisioning team

The team is dedicated to safeguarding our platform against financial crime and ensuring the protection of our legitimate customers. Leveraging cuttingedge machine learning realtime 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 realtime 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  

• Demonstrated experience delivering at least 3 fulllifecycle Java/JVMbased projects each spanning 36 months in duration
• Experience with CI/CD pipelines and Distributed and Concurrent Systems
• Handson experience with Kafka Kafka Streams or Apache Flink
• Experience with OLAP databases or datalakes 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 datadriven decisions to fix customer painpoints
• 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 endtoend ownership of your projects: drive and own them to make sure we hit the goals we want to achieve
• Close collaboration with product managers data scientists data analysts engineers and other product teams is a must have and is something to expect to happen on a daily basis.
• Great communication skills (both verbal and written) and the ability to articulate complex technical concepts to nontechnical audience
• Handson experience working with relational and nonrelational 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
• Being able to propose technical solutions that optimise for latency and throughput at the same time aka: p99 endtoend latency is under 1 second for realtime payment fraud checks even when a significant amount of transactions are in the system.

What does success look like

• Youll be having a real world impact by building financial crime prevention systems which protect customers from falling victims of fraud or scams
• Youll have onboarded and found your place through understanding your team and tribe vision and how you can contribute
• Youll understand how our values can help you guide your work
• Youll understand the reasons behind problematic payments and customer difficulties and how to go about solving them
• Youll be raising the automation level to enable scaling of the product
• Understand our customers and the impact our product makes in their lives 
• Youll help us scaleup and build a world class money transfer product by finding solutions to our technical challenges and opportunities

Additional Information :

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

Were 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 its like to work at Wise visit Wise.Jobs.

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

Remote Work :

No

Employment Type :

Fulltime