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
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
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.