Hybrid opportunity at
WiseLead Data Scientist - AML Handling
Wise is hiring a full-time Lead Data Scientist, graded IC3, for its Anti-Money Laundering Handling and Prevent team in London. The role is hybrid. The team…
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About This Role
Wise is hiring a full-time Lead Data Scientist, graded IC3, for its Anti-Money Laundering Handling and Prevent team in London. The role is hybrid. The team works on the intelligence layer that powers Wise's operational handling and prevention work, automating parts of those systems, building robust evaluation pipelines for large language models, and developing solutions that lower financial crime exposure. The work covers developing AI models that support operational workflows,…
Job Description
Wise is hiring a full-time Lead Data Scientist, graded IC3, for its Anti-Money Laundering Handling and Prevent team in London. The role is hybrid. The team works on the intelligence layer that powers Wise's operational handling and prevention work, automating parts of those systems, building robust evaluation pipelines for large language models, and developing solutions that lower financial crime exposure.
The work covers developing AI models that support operational workflows, particularly enhanced due diligence (EDD) for business and consumer customers. Automation is aimed at summarising cases, raising red flags, sorting risk levels and generating document requests. The lead defines labelling taxonomies with EDD subject-matter experts, builds evaluation datasets, and implements automated evaluation harnesses that score correctness, precision, recall and the ways a system fails. Prompt experiments are run in a hypothesis-driven way to cut down on invented content, formatting slips and drift. The role also includes shadow-mode deployments to test prompts safely at scale, post-release checks for data and output drift, and writing and deploying Python services that run in production. AI supplies recommendations and drafts, while human operators keep the final say on critical assessments. Studying upstream data to head off attempts before they reach operations, and mentoring senior and junior data scientists, are also part of the remit.
The posting asks for hands-on work building, training, testing and assessing machine learning systems, and strong Python skills. Object-oriented programming knowledge is a big plus. Candidates should have built and assessed generative AI and LLM solutions, including automated evaluation and prompt engineering, plus statistics, experiment design and analysis of how LLM systems fail. A product mindset, the ability to work independently across teams, and clear communication with non-technical people and subject-matter experts are required.
Responsibilities
- Lead AI model development for enhanced due diligence workflows, such as case summaries and red-flag generation
- Define labelling taxonomies with subject-matter experts and build evaluation datasets
- Build automated evaluation harnesses that measure correctness, precision, recall and failure patterns
- Run hypothesis-driven prompt experiments to reduce invented content and drift
- Design shadow-mode deployments and post-release monitoring
- Write and deploy Python services that run in production
- Design systems in which human operators keep the final decision
- Study upstream data to stop suspicious activity before it lands in operations
- Set technical direction and mentor data scientists
Requirements
- Hands-on work building, training, testing and assessing machine learning systems
- Strong Python skills
- Experience building and evaluating generative AI and LLM solutions
- Statistics, experiment design and analysis of how LLM systems fail
- Strong product mindset and the ability to work independently across teams
- Clear communication with non-technical people and SMEs
- Problem-solving that refines unclear problem statements into workable solutions
Qualifications
- Object-oriented programming knowledge (a big plus)
- Experience with LLM fine-tuning or reinforcement-based alignment (nice to have)
- Familiarity with agent orchestration tools such as LangGraph (nice to have)
- Working knowledge of Java (nice to have)
- Experience reading historical operational cases (nice to have)
Core Skills
Benefits
- Equity in a profitable company
- Flexible hybrid working arrangements
- Annual personal development budget
- Visa and relocation support
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?
The role is based in London and is hybrid.
What technical skills are needed?
The posting asks for strong Python skills and experience implementing and evaluating machine learning systems, plus generative AI and LLM evaluation experience.
Is visa support offered?
The listed benefits include visa and relocation support.
Is a salary listed?
The posting does not specify a salary or pay range.
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