At a Glance
- Tasks: Lead data strategy and evolve Monzo for seamless money management.
- Company: Join a fast-growing, innovative bank transforming traditional banking.
- Benefits: Competitive salary, performance incentives, flexible hours, and a £1,000 learning budget.
- Other info: Diverse and inclusive workplace with excellent career growth opportunities.
- Why this job: Shape the future of banking with data-driven decisions and impactful projects.
- Qualifications: Experience in data science, strategic thinking, and mentoring skills.
The predicted salary is between 95000 - 130000 £ per year.
London, Cardiff or Remote in the UK | £95,000 to £130,000 | Incentive Awards tied to your performance + Benefits | Technology - Data
We’re waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts, accounts for 16-17 year olds, a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save, invest and combine their pensions with us. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We’re not about selling products - we want to solve problems and change lives through Monzo.
We're looking for a Lead Data Scientist excited to help build the bank of the future. You'll have the opportunity to super charge our user engagement in 2026 and help us to build a bank that customers truly love. At Monzo, we're building a bank that is fair, transparent and a delight to use. We’re growing extremely fast and have over 11 million customers in the UK. We’ve built a product that people love and more than 80% of our growth comes from word of mouth and referrals.
Enable Monzo to Make Better Decisions, Faster
We have a strong culture of data-driven decision making across the whole company. And we're great believers in powerful, real-time analytics and empowerment of the wider business. All our data lives in one place and is super easy to use. 90% of day-to-day data-driven decisions are covered by self-serve analytics through Looker which gives data scientists the head space to focus on more impactful business questions and analyses.
How we hire
We are excited to be expanding and are hiring for multiple roles across our Data Science teams! Whether your interests lie in Borrowing, Growth, Payments, Fincrime, Wealth, or Core, we are looking for talented individuals with a versatile skill set to contribute across our squads. While we allocate teams after the interview process, we aim to match your skills and aspirations with the most suitable role. Throughout the process, you will meet team members from across our Data Science collectives, who will guide you through the opportunities available. Join us and be part of shaping our future!
What you’ll be working on:
- Lead the data strategy and continue to evolve Monzo for our customers to make it magically simple to manage money day-to-day
- Develop and execute best practices for experimentation enabling our team to make data informed decisions
- Collaboratively set standards and work with data across Monzo, fostering knowledge sharing and continuously improving data practices.
- Work closely with leaders in product, engineering, design and research to build and iterate on product ideas
You should apply if:
- You enjoy working with cross functional fast moving teams
- You are able to think strategically about commercial products and how decisions using data can unlock more value for our customers
- You are excited about mentoring other data scientists and analytics engineers
- You are excited by experimentation and utilising new data techniques to solve challenging problems
- You want to understand the nuances of our data and are excited about laying the key foundational knowledge for our new products and features
- You are opinionated about how to think about measuring success and are willing to challenge the status quo
The interview process:
- Initial Call
- Technical assessment
- Final Interviews
- Business Fit/Collaboration Case Study
- Technical Interview
Our average process takes around 2-3 weeks but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process. One of our recruiters has written a blog on the process, for extra details, hints and tips please see Data Hiring at Monzo.
What’s in it for you:
- £95,000 to £130,000 + Incentive Awards tied to your performance + Benefits
- We can help you relocate to the UK or Spain
- We can sponsor visas
- This role can be based in our London or Barcelona offices, but we're also open to distributed working within the UK (with ad hoc meetings in London).
- We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.
- Learning budget of £1,000 a year for books, training courses and conferences
- And much more, see our full list of benefits here
- If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
Equal opportunities for everyone
Diversity and inclusion are a priority for us and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog, 2026 Diversity and Inclusion Report and 2025 Gender Pay Gap Report.
We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status. If you have a preferred name, please use it to apply. We don't need full or birth names at application stage.
We are proud supporters of Women in Data. Connect, engage and belong to the largest free female data community in the UK – visit: www.womenindata.co.uk to join our community.
Stay connected! Follow us on LinkedIn for updates on career opportunities and more.
Lead Data Scientist employer: Women in Data®
Women in Data® is an exceptional employer that champions diversity and innovation within the tech industry. With a strong commitment to employee growth, you will benefit from generous annual leave, ongoing development opportunities, and a collaborative work culture that values mentorship and technical excellence. Join us in a role that not only enhances your career but also contributes to meaningful initiatives in data and machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist
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We think you need these skills to ace Lead Data Scientist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at Women in Data®
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.