# Lead Data Scientist - AML Handling

**Company**: Wise
**Location**: London
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Category**: Data Science
**Industry**: Technology

**Apply**: https://jobs.smartrecruiters.com/Wise/744000152971678-lead-data-scientist-aml-handling?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_ec31a9e4-51b

## Description

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.

We're looking for a Lead Data Scientist (IC3) to join our Anti-Money Laundering (AML) Handling & Prevent team in London. This role is a unique opportunity to work on the intelligence system at the core of our operational handling and prevention work. You'll help automate components of our operational systems, establish robust LLM evaluation pipelines, and build solutions that reduce financial crime risk.

As a Lead Data Scientist (IC3), you will drive technical strategy across handling and prevent initiatives, architect robust AI systems, establish post-deployment monitoring, and lead complex automation initiatives to reduce financial crime risk across Wise.

Here's how you’ll be contributing:

- Lead the development and deployment of AI models designed to augment operational workflows, specifically targeting the automation of case summaries, red flag generation, risk classifications, and document requests.

- Establish labeling taxonomies and guidelines with EDD SMEs, construct evaluation datasets, and implement automated eval harnesses to systematically measure accuracy, precision, recall, and failure modes.

- Audit existing prompts and run structured experiments within a hypothesis-driven testing framework to reduce hallucinations, formatting errors, and prompt drift.

- Design shadow mode deployments and parallel execution testing to safely evaluate prompts at scale, while implementing post-deployment monitoring for data and output drift.

- Take ownership of the production pipeline by writing and deploying production-ready Python services.

- Design systems where AI provides recommendations and drafts, ensuring human operators retain the final decision-making authority for critical financial crime mitigation assessments.

- Analyze upstream data to create strategies that deflect financial crime attempts before they reach the operations team, effectively reducing manual workload.

- Set technical direction, mentor Senior and Junior Data Scientists, foster a product-focused mindset, and guide the team through complex technical implementations, architectural decisions, and AI governance standards.

A bit about you:

- Experience implementing, training, testing and evaluating performance of Machine Learning systems;

- Strong Python knowledge;

- Knowledge and experience developing and evaluating GenAI / LLM solutions, including automated eval harnesses and prompt engineering;

- Experience with statistical analysis, experiment design, and failure mode analysis in LLM systems;

- 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 and SMEs;

- 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, for example Large Language Models;

- Experience implementing fine-tuning, reinforced learning alignment and evaluation techniques within an LLM training pipeline;

- Familiarity with agentic frameworks such as LangGraph or similar;

- Willingness to get hands dirty reading many, many historical operational cases;

- Working knowledge of Java.

Key benefits:

- Stock options in a profitable company;

- Hybrid working model;

- Annual personal development budget;

- Visa and relocation support.

## Skills

### Required
- Machine Learning
- Python
- GenAI
- LLM solutions
- statistical analysis
- experiment design
- failure mode analysis

### Nice to have
- Large Language Models
- fine-tuning
- reinforced learning alignment
- evaluation techniques
- LangGraph
- Java

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Source: [Apply at jobs.smartrecruiters.com](https://jobs.smartrecruiters.com/Wise/744000152971678-lead-data-scientist-aml-handling?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)