Lead AI Data Scientist

Posted Yesterday
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London, Greater London, England
Hybrid
Senior level
Fintech • Mobile • Payments • Software • Financial Services
Wise is one of the fastest growing fintechs in the world and we’re on a mission to make money without borders a new norm
The Role
As the Lead AI Data Scientist, you'll automate financial crime risk operations, develop AI models, mentor junior data scientists, and drive enhancements in operational workflows.
Summary Generated by Built In
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.

More about our mission and what we offer.

Job Description

Lead AI Data Scientist - Servicing

We’re looking for a Lead AI Data Scientist to join our Servicing team in London. 

This role is a unique opportunity to work on the intelligence system at the core of our operational handling work. You'll help automate components of our operational systems 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.

 

About the Role: 

The Servicing team offers an exciting environment for applying cutting-edge Generative AI solutions. This team is dedicated to enhancing our financial crime mitigation operations through tooling and automation, aiming to streamline reviews and simplify the work of our operations staff. A core focus involves analyzing and automating significant parts of our operational workflows. Furthermore, the team develops LLM-based tools to assist crime prevention teams in deflecting demand. The successful candidate will have the chance to directly contribute to Wise's mission by tackling these challenges and developing a comprehensive testing suite for our solutions.

 

Here’s how you’ll be contributing: 

  • End-to-End Automation: Lead the development and deployment of AI models designed to augment operational workflows, specifically targeting the automation of case comments, red flag generation, final review summaries, and data labeling.

  • 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.

  • Rigorous Testing & Governance: Establish comprehensive testing frameworks (e.g., shadow mode, A/B testing) for production environments and act as the technical liaison with Compliance to ensure all models meet regulatory standards prior to launch.

  • 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.

  • Mentorship & Leadership: Lead and grow other Junior Data Scientists, fostering a product-focused mindset and guiding them through complex technical implementations and architectural decisions.


     

    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 Unsupervised Learning methods

  • Experience with statistical analysis, and ability to produce well-designed experiments

 

         Some extra skills that are great (but not essential):  
 

  • Hands-on experience training Neural Network models and deploying them into production

  • 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.

 

Additional Information

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.

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.

If you want to find out more about what it's like to work at Wise visit Wise.Jobs.

Keep up to date with life at Wise by following us on LinkedIn and Instagram.

Top Skills

Generative Ai
Llm
Machine Learning
Neural Networks
Python
Unsupervised Learning

What the Team is Saying

Lindsay
Surendra
Smrithi
Pavan
Jennifer
Lauren
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The Company
8,000 Employees
Year Founded: 2011

What We Do

Wise is a global technology company, building the best way to move and manage the world's money.

With Wise Account and Wise Business, people and businesses can hold 40 currencies, move money between countries and spend money abroad. Large companies and banks use Wise technology too; an entirely new network for the world's money. Launched in 2011, Wise is one of the world’s fastest growing, profitable tech companies.

In fiscal year 2025, Wise supported around 15.6 million people and businesses, processing over $185 billion in cross-border transactions and saving customers around $2.6 billion.

Why Work With Us

We’re truly global in who we are, how we work, and how we build. Everything we do is centred around creating a world of money that’s fast, easy, fair. And open to all. Everyone who works here owns a piece of Wise, from the work they do, to the stock they hold.

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Wise Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

We expect new joiners in the office most days to build connections and learn from colleagues for their first six months. After that, most Wisers split their working week between the office and home, typically coming in at least 12 times a month.

Typical time on-site: Not Specified
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