Lead Data Scientist - Contact Automation

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London, England
Hybrid
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
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 Lead Data Scientist 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.

In the near-term our Data Science members are primarily focused on developing the foundation of the customer problem understanding system. There are many interesting research angles, especially within the NLP domain. 

Here’s how you’ll be contributing:

  • Customer Problem Understanding System Development
    • Analysing contact data to identify patterns and uncover underlying structures
    • Creating automated algorithms for extracting information from real customer interactions
    • Developing the system’s ability to learn which data points are key to resolving specific customer problems
    • Innovating prompt development to optimise the performance of LLM-based parts of the system and background processes
    • Developing models to map customer contacts to defined structures
  • Performance Testing and Optimisation
    • Evaluating our customer problem understanding system against internal and external benchmarks
    • Identifying and categorising system errors, and suggesting technical solutions to rectify these errors
    • Fine-tuning system settings to achieve an optimal balance between precision and recall
    • Providing data-driven insights on potential outcomes under various scenarios
  • Operational Process Development
    • Collaborating with operational teams to refine processes, ensuring effective feedback integration into our automation systems
    • Designing and managing projects that utilise excess operational capacity, such as manual data labelling for model improvement
  • Enhancing Learning Processes
    • Integrating active learning strategies to continuously improve model accuracy through feedback loops
  • Deployment and Implementation
    • Packaging algorithms into deployable libraries/objects and transitioning them from staging to production environments
    • Implementing and maintaining scheduled processes for data gathering and model retraining using automated pipelines
    • Maintaining production-grade Python services

A bit about you: 

  • Demonstrated experience in developing and deploying production-grade Machine Learning or Data Science solutions that operate at scale and directly shape the user experience, ideally forming the core of user interactions.
  • Prior experience building solutions within the Customer Support and/or Chatbot domain is highly advantageous, with experience in the FinTech sector being a significant plus.
  • 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;
  • A strong product mindset with the ability to work independently in a cross-functional and cross-team environment;
  • 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):  

  • 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
  • Willingness to get hands dirty reading many, many historical chat transcripts
     

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.

Additional Information

Key benefits:

  • Stock options in a profitable company
  • 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.

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.

What the Team is Saying

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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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