About the company
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.
Responsibilities
- 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.
- 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.
- 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.
- 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.
Requirements
- 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 t