Wise
From Wise's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
As part of our team, you will be helping us create an entirely new network for the world's money.
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 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.
In the Anti-Money Laundering (AML) Risk team we are developing systems which are a mixture of unsupervised and supervised learning, with GenAI to detect and mitigate Financial Crime on a global scale. You will be working on cutting-edge technology to sustainably support Wise’s growing customer, transaction and product space.
AML Risk Detection System Development
Developing efficient and effective AML detection controls using a mixture of unsupervised, semi-supervised and supervised learning with GenAI
Creating frameworks to prove controls coverage at a regional level
Developing technologies to serve Wise’s diverse international user base
Working in Cross-Functional Teams
Working across functions to own and solve AML related problems at a global scale
Mentoring more junior members of the team on technical and non-technical skillsets
Performance Testing and Optimisation
Evaluating our AML systems against internal and external benchmarks
Developing decisioning layers to find optimal trade-offs between precision and recall
Providing data-driven insights on potential outcomes under various scenarios
Operational Process Development
Collaborating with operational teams to refine processes, ensuring effective feedback integration into our automation systems
Designing and managing projects that utilise excess operational capacity, such as manual data labelling for model improvement
Creating systems which provide in-depth insight to investigators on red flags and typologies present on profiles/transactions
Deployment and Implementation
Packaging algorithms into deployable libraries/objects and transitioning them from staging to production environments
Implementing and maintaining scheduled processes for data gathering and model retraining using automated pipelines
Maintaining production-grade Python services
Experience implementing, training, testing and evaluating performance of Machine Learning systems;
Strong Python knowledge. A big plus for proven familiarity and experience with OOP principles;
Experience with statistical analysis, and ability to produce well-designed experiments;
A strong product mindset with the ability to work independently in a cross-functional and cross-team environment;
Good communication skills and ability to get the point across to non-technical individuals;
Strong problem solving skills with the ability to help refine problem statements and figure out how to solve them.
Familiarity with automating operational processes via technical solutions, for example Large Language Models
Willingness to get hands dirty with operational side by sides to understand their pain points
Knowledge and experience within the Financial Crime domain
We’re people without borders — without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you’re passionate about learning new things and keen to join our mission, you’ll fit right in.
Also, qualifications aren’t that important to us. If you’ve got great experience, and you’re great at articulating your thinking, we’d like to hear from you.
And because we believe that diverse teams build better products, we’d especially love to hear from you if you’re from an under-represented demographic.
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.
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