Lead Data Scientist - Marketing

Posted Yesterday
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London, Greater London, England, GBR
Hybrid
Mid 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
The Lead Data Scientist will contribute to Marketing by developing predictive models for Customer Lifetime Value and Marketing Mix Models, guiding growth strategies based on data analysis and collaboration with Data Analysts and Marketing teams.
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

Your mission: 

Wise has already pioneered new ways for people to transfer money across borders and currencies. Our customers can also manage their hard-earned money with the world’s first platform to offer true multi-currency banking. Your mission is to help make people aware of Wise as a solution for cross-border money needs.

Here’s how you’ll be contributing to Marketing

  • You will help the Marketing tribe find the biggest opportunities for growth

  • You will help us understand in what growth activity to invest (Marketing Mix Models) and how to reduce the uncertainty on marketing measurement 

  • You will do this by developing predictive models to calculate Customer Lifetime Value (LTV), aiding in the prioritization of marketing efforts and resource allocation. 

  • You will model customer behaviour data and product usage so we understand which audiences to target and how

  • You will work closely with Data Analysts and you will help them understand and use models that you build (LTV or MMM models)

  • Your average day will include building new models, maintaining models used by everyone in the marketing tribe, evaluating new ideas and communicating what models can tell us about how and why we grow

This role will give you the opportunity to: 

  • Have a direct impact - You will closely partner with every marketing team within both Organic and Paid Acquisition and help millions of people and businesses to learn about how Wise can help them

  • Work autonomously - we believe people are most empowered when they can act autonomously. So rather than telling you what to do, you’ll work with your team to create a vision of your own. Of course, you can always gather feedback from smart, curious people across Wise but you’ll have the freedom to make your own calls.

  • Be part of a diverse team - You will work in a team of Data scientists, Analysts and Marketeers

  • Be part of our mission to make money without borders the new normal

 

 

Qualifications

About you: 

  • You have expert knowledge of Python, and are able to make and justify design decisions in your Python code.

  • You have built Marketing Mix Modelling (MMM) models and you are able to translate the results into actionable strategies.

  • You have experience in building lifetime value (LTV) models.

  • You are familiar with a range of model types, and know when and why  to use gradient boosting, neural networks, good old linear regression, or a blend of these

  • You have a proficient understanding of statistics, in particular Bayesian reasoning

  • You are able to take ownership of a project and see it through from end to end, with past experience in doing so

  • You are data-driven with a structural approach. You need to be able to prioritise the value you can add, and manage your time effectively.

  • You see a bigger picture of business processes and can cut through vagueness to define precisely where and how a model would fit into our stack and what value it would add.

  • You are comfortable with visualising and communicating data to various audiences, you easily articulate and present your ideas.

 

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

  • You have a good understanding of causal inference concepts and have some experience with machine learning models for causal inference

  • You have hands-on experience evaluating marketing campaigns through incrementality testing and geo-experiments.

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.

Skills Required

  • Expert knowledge of Python
  • Experience building Marketing Mix Modelling (MMM) models
  • Experience in building Lifetime Value (LTV) models
  • Proficient understanding of statistics, especially Bayesian reasoning
  • Ability to own projects and see through from start to finish

What the Team is Saying

Surendra
Smrithi
Pavan
Jennifer
Lindsay
Lauren
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The Company
9,000 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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