Data Scientist - Growth & Strategic Finance

Wise
London
11 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist - Measurement Specialist

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 and .

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 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 .

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

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.