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Wise

Data Science Lead - Contact Automation

Posted 4 Days Ago
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Hybrid
London, Greater London, England, GBR
Mid level
Hybrid
London, Greater London, England, GBR
Mid level
As a Data Science Lead, you will develop and optimize a contact automation system, improve customer interactions, and work cross-functionally to drive product decisions and enhancements.
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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

We’re looking for a Data Science Lead to join our Contact Automation team in London. 

This role is a unique opportunity to work on the intelligence system at the core of our contact automation system. Your work will make our system aware of the different problems our customers encounter and eventually develop the ability to help customers resolve these issues. What you build will have a direct impact on Wise’s mission and millions of our customers.
 

About the Role: 

In the Support squad we are aiming to create a system that can power an automated “Wise Assistant” system that can answer most customer questions within the chat interface effectively, as well as support our agents in answering more complex questions. 

To achieve our targets we need to have applied this system effectively at scale, across the large majority of our contacts working seamlessly within the chat interface.

Moving money should not be difficult. As a Data Science Lead in contact automation, your work will have a direct impact on customers - helping millions of people send and receive money across borders.
 

Here’s how you’ll be contributing:

Evaluation & Experimentation (Core Focus)

  • Own the design and evolution of evaluation frameworks for LLM-based systems (both offline and online)

  • Build and scale A/B testing to measure real customer impact and guide product decisions

  • Define meaningful metrics that connect system performance to customer outcomes and business impact

System Performance & Reliability

  • Identify failure modes across the assistant (reasoning, retrieval, tool use, tone, etc.) and drive improvements

  • Work closely with engineers to iterate on agentic workflows. 

  • Continuously improve system behaviour through prompt design, evaluation insights, and data-driven iteration

  • Ensure the system performs reliably across multiple languages and geographies

Opportunity Identification

  • Analyse conversation data to uncover new opportunities for improving the customer experience.

  • Proactively shape what we should build next.

  • Bring clarity to ambiguous problem spaces and turn them into actionable changes to the system

Cross-functional Collaboration

  • Work daily with Product, Engineering, and Content/Design to shape the assistant’s behaviour

  • Influence decisions about the product through clear communication, data visualisations, and well-structured impactful proposals.

  • Ensure the system is not only accurate, but intuitive and trustworthy from a customer perspective.

How You’ll Work

  • You will operate with a high degree of autonomy in a fast-moving environment (often working on 1–2 week iteration cycles) in close collaboration with engineering, content and product.

  • Use feedback loops—both human and system-generated—to continuously improve performance

  • Take ownership beyond your immediate scope when needed to move the project forward

Qualifications

  • Strong sense of ownership; you drive work from idea to production and are motivated by building real systems used by customers. 

  • Good communicator, you are able to present ideas and foster discussion with both technical and non-technical audiences

  • Strong grounding in statistics, with the ability to design, run and own A/B testing and experimentation end-to-end. 

  • Strong understanding of how to evaluate models (classification, regression, or LLMs) and why metrics matter and a proven ability to connect model/system performance to business outcomes.

  • A strong product mindset and ability to work collaboratively in a cross-functional environment.

  • Experience writing production code in at least one of Python, TypeScript or Java.

  • Familiarity with modern LLM/agentic architectures (e.g. Mastra, LangGraph or similar frameworks)

  • Strong data skills (SQL, snowflake, data visualisation).

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

  • Experience with a customer facing agentic system.

  • Experience with Bayesian inference, especially with  A/B testing.

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.

Wise London, England Office

London, United Kingdom

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