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Lead Data Scientist - AML

Reads like a ML Engineer role: putting models into production.

London, United Kingdom

Pay
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Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
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Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
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What you’ll work on

Full posting

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.

Developing efficient and effective AML detection controls using a mixture of unsupervised, semi-supervised and supervised learning with GenAI

  • Develop AML detection controls using unsupervised, semi-supervised and supervised learning with GenAI

  • Evaluate AML systems against internal and external benchmarks and tune precision-recall trade-offs

  • Package algorithms into deployable libraries and move them from staging to production

  • Maintain automated pipelines for data gathering and model retraining

  • Build systems that give investigators insight into red flags and typologies

From the employer’s posting
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.
Developing efficient and effective AML detection controls using a mixture of unsupervised, semi-supervised and supervised learning with GenAI
Evaluating our AML systems against internal and external benchmarks
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
Creating systems which provide in-depth insight to investigators on red flags and typologies present on profiles/transactions

What you’ll bring

All qualifications

Core experience

  • Experience implementing, training, testing and evaluating performance of Machine Learning systems;
  • Experience with statistical analysis, and ability to produce well-designed experiments;
  • Good communication skills and ability to get the point across to non-technical individuals;
  • Familiarity with automating operational processes via technical solutions, for example Large Language Models
  • Knowledge and experience within the Financial Crime domain
Qualification wording
Experience implementing, training, testing and evaluating performance of Machine Learning systems;
Experience with statistical analysis, and ability to produce well-designed experiments;
Good communication skills and ability to get the point across to non-technical individuals;
Familiarity with automating operational processes via technical solutions, for example Large Language Models
Knowledge and experience within the Financial Crime domain

Tools in this posting

  • Python
Source — Tool mentions in context
- Implementing and maintaining scheduled processes for data gathering and model retraining using automated pipelines - Maintaining production-grade Python services Qualifications
- 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;

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Live
First seen by us
Oct 19, 2026 · 10 days ago
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Last seen by us
Oct 29, 2026
Reposted
once since Oct 15, 2026

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Job description

View original posting ↗

Job Description

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 working on cutting-edge technology to sustainably support Wise’s growing customer, transaction and product space.

 

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

 

Qualifications

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

 

Additional Information

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.

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.

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London, United Kingdom

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