We're looking for a Data Science Lead to join our AML Risk team in London. This role is a unique opportunity to build 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. Your work will allow Wise to keep our customers safe and 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 that mix unsupervised, supervised learning and GenAI to detect and mitigate Financial Crime on a global scale. You will ensure 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.
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 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; experience with OOP principles is a plus
- Experience with statistical analysis and the 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, e.g., Large Language Models
- Willingness to get hands dirty with operational side by side to understand pain points
- Knowledge and experience within the Financial Crime domain