Lead Data Scientist - AML Handling

SmartRecruiters, Inc.; Greater London; Hybrid; GBP 91,000 - 127,000; Full time

Benefits offered by this job

Hybrid working model

Annual personal development budget

Visa and relocation support

Job summary

Wise is seeking a Lead Data Scientist (IC3) for the AML Handling & Prevent team in London. You will architect AI systems, automate case workflows, and build post‑deployment monitoring to reduce financial crime risk.

You’ll lead and mentor a skilled team while shaping the technical strategy and governance around GenAI and ML systems. The role emphasizes end‑to‑end production pipelines, robust evaluation, and collaboration with cross‑functional teams.

Qualifications

• Experience implementing, training, testing and evaluating performance of ML systems.
• Strong Python knowledge with object‑oriented design.
• Experience developing GenAI / LLM solutions, with automated eval harnesses.
• Experience with statistical analysis, experimental design and failure mode analysis in LLM systems.
• Product mindset and ability to work across teams.
• Clear communication with non-technical SMEs.
• Strong problem solving and analytical skills.

Responsibilities

• Lead end‑to‑end automation and EDD LLM work to augment operational workflows.
• Define evaluation datasets, labeling taxonomy, and automated eval harnesses.
• Audit prompts and run structured experiments to reduce hallucinations and drift.
• Design shadow testing and post‑deployment monitoring for data and output drift.
• Own production Python services and drive rapid value while keeping quality.
• Design human‑in‑the‑loop systems and governance for ML solutions.
• Develop strategies to deflect financial crime upstream and reduce manual work.
• Provide technical leadership and mentor Senior and Junior Data Scientists.

Skills

Python

GenAI / LLM

Prompt engineering

Machine learning

Leadership

Mentorship

Communication

Tools

LangGraph

Java

Job description

• Compensation: GBP 90,500 - GBP 127,000 - yearly

Company 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.

As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.

Lead Data Scientist - Anti-Money Laundering (AML) Handling & Prevent

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. What you build will have a direct impact on Wise’s mission and millions of our customers.

The AML Handling & Prevent team offers an exciting environment for applying cutting-edge Generative AI solutions and machine learning architectures. This team is dedicated to enhancing our financial crime mitigation operations through advanced tooling, automated evaluation frameworks, and prompt optimization, aiming to streamline reviews and simplify the work of our operations staff. 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:

• End-to-End Automation & EDD LLMs: Lead the development and deployment of AI models designed to augment operational workflows (e.g. Business and Consumer EDD LLMs), specifically targeting the automation of case summaries, red flag generation, risk classifications, and document requests.
• Evaluation Framework & Labeling Taxonomy: 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.
• Prompt Optimization & Experimentation: Audit existing prompts and run structured experiments (few-shot, chain-of-thought, context ordering) within a hypothesis-driven testing framework to reduce hallucinations, formatting errors, and prompt drift.
• Shadow Testing & Monitoring: Design shadow mode deployments and parallel execution testing to safely evaluate prompts at scale, while implementing post-deployment monitoring for data and output drift.
• Full-Stack Deployment: Take ownership of the production pipeline by writing and deploying production-ready Python services. You must be willing to bypass engineering bottlenecks to ship value quickly while maintaining code quality.
• Human-in-the-Loop Architecture: Design systems where AI provides recommendations and drafts, ensuring human operators retain the final decision-making authority for critical financial crime mitigation assessments.
• Strategic Demand Deflection: Go beyond ticket handling by analyzing upstream data to create strategies that deflect financial crime attempts before they reach the operations team, effectively reducing manual workload.
• Technical Leadership & Mentorship: 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. A big plus for proven familiarity and experience with OOP principles;
• 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.

We’re people without borders — without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you’re passionate about learning new things and keen to join our mission, you’ll fit right in.

Also, qualifications aren’t that important to us. If you’ve got great experience, and you’re great at articulating your thinking, we’d like to hear from you.

And because we believe that diverse teams build better products, we’d especially love to hear from you if you’re from an under-represented demographic.

• Hybrid working model - whether it’s working from home, working overseas, school plays or life admin we get that flexibility is essential
• Annual personal development budget - whether it’s for books, courses, or conferences
• Visa and relocation support

You can read more about our full benefits package here ...

For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.

We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.