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WiseLead Data Scientist - AML
Wise is seeking a Lead Data Scientist for its Anti-Money Laundering Risk team based in London. This on-site role involves building systems that combine supervised and…
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About This Role
Wise is seeking a Lead Data Scientist for its Anti-Money Laundering Risk team based in London. This on-site role involves building systems that combine supervised and unsupervised learning alongside generative AI to detect and mitigate financial crime globally. The successful candidate will work on advanced technology designed to support a growing customer base, diverse product offerings, and high transaction volumes. This position suits a professional with strong programming skills and…
Job Description
Wise is seeking a Lead Data Scientist for its Anti-Money Laundering Risk team based in London. This on-site role involves building systems that combine supervised and unsupervised learning alongside generative AI to detect and mitigate financial crime globally. The successful candidate will work on advanced technology designed to support a growing customer base, diverse product offerings, and high transaction volumes.
This position suits a professional with strong programming skills and experience in evaluating machine learning systems. Responsibilities span across functional teams to tackle global AML challenges, mentor junior colleagues, evaluate system performance, and optimize decision-making layers. The role also requires close collaboration with operational units to refine automation processes, design data-labeling projects, and package algorithms into production-ready Python services.
Responsibilities
- Develop efficient anti-money laundering detection controls utilizing supervised, semi-supervised, and unsupervised machine learning methods along with generative AI
- Build regional frameworks to demonstrate controls coverage
- Collaborate across multiple functions to solve global anti-money laundering problems
- Mentor junior team members on both technical and non-technical skills
- Benchmark anti-money laundering systems against internal and external standards
- Construct decisioning layers to balance precision and recall
- Partner with operations to refine processes and integrate feedback into automation systems
- Design and manage projects utilizing excess operational capacity for manual data labelling
- Build systems providing deep investigator insights regarding red flags and typologies
- Package algorithms into deployable libraries and manage transitions from staging to production
- Implement and maintain automated pipelines for data collection and model retraining
- Maintain production-grade Python services
Requirements
- Experience in implementing, training, testing, and evaluating the performance of machine learning systems
- Strong proficiency in Python
- Experience with statistical analysis and the design of well-structured experiments
- Product mindset with the capacity to operate independently in cross-functional environments
- Communication skills suitable for conveying points to non-technical audiences
- Problem-solving abilities to refine problem statements and determine solutions
Qualifications
- Familiarity with object-oriented programming principles
- Experience automating operational processes through technical solutions like large language models
- Willingness to engage directly with operational side-by-sides to understand pain points
- Knowledge and practical background in the financial crime domain
Core Skills
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where is this job located?
This on-site role is located in London.
What is the employment type?
The posting specifies full-time employment.
What salary is offered for this role?
The salary is not stated in the job posting.
What technical background is required?
Candidates must have strong Python knowledge, experience implementing and evaluating machine learning systems, statistical analysis skills, and a product mindset.
Sample Interview Questions
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