At a Glance
- Tasks: Join our team to analyse data, build predictive models, and drive strategic decisions.
- Company: Wise is a global tech company revolutionising how money is moved and managed worldwide.
- Benefits: Enjoy a diverse and inclusive workplace with opportunities for growth and remote work options.
- Why this job: Make a real impact on millions of customers while working in a dynamic, innovative environment.
- Qualifications: Experience in machine learning, Python, and financial modelling is preferred; strong communication skills are essential.
- Other info: We celebrate diversity and empower every team member to contribute to our mission.
The predicted salary is between 36000 - 60000 £ per year.
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.
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 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.
Data Scientist - Growth & Strategic Finance employer: Wise
Contact Detail:
Wise Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Growth & Strategic Finance
✨Tip Number 1
Familiarise yourself with Wise's mission and values. Understanding their commitment to making money management easier for everyone will help you align your answers during interviews and demonstrate your passion for their goals.
✨Tip Number 2
Brush up on your Python skills, especially in relation to data analysis and machine learning. Being able to showcase your technical abilities in these areas will be crucial, as they are key components of the role.
✨Tip Number 3
Prepare to discuss specific examples of how you've used data analytics to drive business decisions in previous roles. This will highlight your practical experience and ability to translate complex data into actionable insights.
✨Tip Number 4
Network with current or former employees of Wise on platforms like LinkedIn. Gaining insights from their experiences can provide you with valuable information about the company culture and expectations, which can be beneficial during your application process.
We think you need these skills to ace Data Scientist - Growth & Strategic Finance
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data analysis, predictive modelling, and machine learning. Use specific examples that demonstrate your skills in financial modelling and collaboration with cross-functional teams.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for Wise's mission and how your background aligns with the role. Mention specific projects or achievements that showcase your ability to drive data-driven decision-making.
Showcase Technical Skills: Clearly outline your proficiency in Python and any other relevant programming languages or tools. Provide examples of how you've used these skills in previous roles, particularly in building and deploying machine learning models.
Prepare for Potential Assessments: Be ready for technical assessments or case studies that may be part of the application process. Brush up on your data analysis techniques and be prepared to discuss your approach to solving complex problems.
How to prepare for a job interview at Wise
✨Showcase Your Data Skills
Be prepared to discuss your experience with data analysis, predictive modelling, and machine learning. Bring examples of projects where you've successfully applied these skills, especially in a financial context.
✨Understand the Company’s Mission
Wise is all about making money management easier for everyone. Familiarise yourself with their services and think about how your role as a Data Scientist can contribute to this mission. This will show your genuine interest in the company.
✨Prepare for Technical Questions
Expect questions that test your knowledge of Python and data engineering principles. Brush up on your coding skills and be ready to solve problems on the spot, as this demonstrates your technical proficiency.
✨Communicate Clearly
You’ll need to explain complex data insights to non-technical stakeholders. Practice articulating your findings in a clear and concise manner, focusing on how your insights can drive business decisions.