Job Description

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

Are you interested in this position?

Apply by clicking on the “Apply Now” Button below!
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