Lead Data Scientist - Anti-Money Laundering (AML)

Here’s how you’ll be contributing:

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

A bit about you:

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.

Some extra skills that are great (but not essential):

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.

Office: London

Key benefits:

Stock options in a profitable company

Hybrid working model - whether it’s working from home, working overseas, school plays or life admin we get that flexibility is essential

Annual personal development budget - whether it’s for books, courses, or conferences

Visa and relocation support

You can read more about our full benefits package here...

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.

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