Data Science Lead - AML Risk

We’re looking for a Data Science Lead to join our AML Risk team in London.

This role is a unique opportunity to work on building out the lead Data Science team and machine learning based technical solutions in the AML Risk team, which owns AML detection across all of the Wise licenses. This is an exciting opportunity to develop the program in a global company. Your work will allow Wise to keep our customers safe and making sure we can keep our ecosystem free of bad actors in a scalable way. What you build will have a direct impact on Wise’s mission and millions of our customers.

About the Role:

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 making sure the AML Risk Data Science team is well equipped and working on cutting-edge technology to sustainably support Wise’s growing customer, transaction and product space.

You will be stepping into an already functioning, but growing product team.

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

Building a team of high performing specialists

Working with product managers and engineering leads to understand staffing requirements

Hiring specialists

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.

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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