Hybrid opportunity at
WiseLead Data Scientist - Anti-Money Laundering (AML)
The Lead Data Scientist role sits in Wise's Anti-Money Laundering team in London. It is a full-time, hybrid position. The team builds systems that blend label-free,…
Career Tools
About This Role
The Lead Data Scientist role sits in Wise's Anti-Money Laundering team in London. It is a full-time, hybrid position. The team builds systems that blend label-free, partly labelled and fully labelled model training with GenAI to catch and reduce financial crime worldwide. The aim is to keep customers safe and the platform clear of bad actors while scaling alongside a growing base of customers, transactions and products. The work covers…
Job Description
The Lead Data Scientist role sits in Wise's Anti-Money Laundering team in London. It is a full-time, hybrid position. The team builds systems that blend label-free, partly labelled and fully labelled model training with GenAI to catch and reduce financial crime worldwide. The aim is to keep customers safe and the platform clear of bad actors while scaling alongside a growing base of customers, transactions and products.
The work covers detection, operations and deployment. The lead develops AML detection controls, builds frameworks that show control coverage at regional level, and creates decisioning layers that balance precision against recall. Systems are evaluated against internal and external benchmarks, and scenario-based insights are provided with data. The role works with operational teams to feed investigator experience into automation, creates systems that give investigators insight into red flags and typologies, and designs projects that use spare operational capacity, such as manual labelling for model improvement.
Deployment is part of the job too: packaging algorithms into deployable libraries, moving them from staging into production, and maintaining scheduled retraining pipelines and production-grade Python services. The posting seeks hands-on experience implementing, training and evaluating machine learning systems, strong Python skills, and knowledge of statistical analysis and experimental design. A product mindset, independent work across teams, and the ability to explain technical ideas to non-technical people are key. Mentoring junior colleagues is also expected. The posting says qualifications matter less than experience and clear thinking.
Responsibilities
- Develop AML detection controls using unsupervised, semi-supervised, supervised and GenAI methods
- Build frameworks that prove control coverage at regional level
- Create decisioning layers that balance precision and recall
- Test AML systems against benchmarks both inside and outside the company
- Work with operations teams to feed investigator feedback into automation
- Package algorithms into deployable libraries and move them into production
- Maintain scheduled data gathering and model retraining pipelines and production Python services
- Mentor more junior team members on technical and non-technical skills
Requirements
- Hands-on background building, fitting, checking and assessing machine learning systems
- Strong Python skills
- Experience with statistical analysis and well-designed experiments
- Strong product mindset and the ability to work independently across teams
- Good communication with non-technical audiences
- Strong problem solving, including refining problem statements
Qualifications
- Familiarity with object-oriented programming principles (a big plus)
- Familiarity with automating operational processes through technical solutions such as large language models
- Willingness to work alongside operational teams to understand their pain points
- Knowledge of or experience in the financial crime domain
Core Skills
Benefits
- Stock options at a profitable company
- Hybrid working model
- Annual personal development budget for books, courses or conferences
- Visa and relocation support
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is the role hybrid?
Yes. The posting describes a hybrid working model based in London.
Is visa support available?
Yes. The posting lists visa and relocation support as a benefit.
What is the core technical requirement?
Strong Python and hands-on experience with machine learning systems are the core requirements.
Is a salary stated?
The posting does not specify a salary.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.