Data Scientist - Growth & Strategic Finance

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London, Greater London, England, GBR
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 Data Scientist to join our growing Growth & Strategic Finance Team in London. 

This role is a unique opportunity to work behind the scenes of company transactions, understand how we grow and at the same time provide our customers with the seamless service they deserve. What you build will have a direct impact on Wise’s mission and millions of our customers.

We are seeking a skilled and detail-oriented Data Scientist to join our Financial Planning and Analysis (FP&A) team. This role will drive data analytics, build predictive models, and leverage machine learning to support strategic decision-making across the whole company. 

As a member of the FP&A team, you will partner closely with finance, operations, and product teams to uncover insights, forecast trends, and identify areas for operational efficiency and revenue growth. This position offers a unique opportunity to influence business strategy by transforming complex datasets into actionable insights, enabling data-driven decision-making across the organisation.

Here’s how you’ll be contributing:

  • Data Analysis and Visualization

    • Collect, clean, and process large financial and operational datasets from multiple sources.

    • Develop and maintain interactive dashboards, reports, and visualisations to provide clear and actionable insights for FP&A stakeholders.

    • Leverage statistical methods to analyse trends, measure business performance, and assess financial impacts.

  • Predictive Modeling & Forecasting

    • Design and build predictive models and machine learning algorithms to forecast key financial metrics, including revenue, expenses, profitability, and cash flow. 

    • Develop scenario analyses and sensitivity models to support budgeting, forecasting, and long-term financial planning processes.

    • Work with finance team members to embed models within FP&A processes, improving forecasting accuracy and decision-making capabilities.

  • Operational Efficiency & Automation

  • Identify and implement automation opportunities within data collection, reporting, and financial planning processes.

  • Build data pipelines and improve data infrastructure, ensuring that accurate and timely data is accessible.

  • Data Quality & Governance

    • Ensure data integrity and accuracy by implementing robust data validation techniques.

    • Train and educate team members on best practices for data usage and reporting.

  • Strategic Insights and Business Impact

    • Perform ad-hoc analyses to provide actionable insights for senior leadership on specific business questions or strategic initiatives.

    • Collaborate closely with cross-functional teams to understand business needs, translate them into analytical questions, and deliver insights that drive business performance.

    • Communicate findings and recommendations in a clear, concise manner to both technical and non-technical audiences.

A bit about you: 

  • Demonstrated experience building and deploying machine learning models in a business environment. Experience with financial modelling, forecasting, and scenario analysis is a plus

  • Strong Python knowledge and software engineering skills. Ability to read through code. Demonstrable experience collaborating with engineering and analytics;

  • A strong product mindset with the ability to work independently in a cross-functional and cross-team environment;

  • Great communication and presentation skills and ability to get the point across to non-technical individuals;

  • Strong problem solving skills with the ability to help refine problem statements and figure out how to solve them.

Additional Information

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

Surendra
Smrithi
Pavan
Jennifer
Lindsay
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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