🚀 We’re on a mission to make money work for everyone.
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 ❤️
📍London/Cardiff/UK Remote | 💰 £113,200 - £153,200 + Incentive Awards tied to your performance + Benefits ✨
Our Financial Crime and Fraud Team ⭐
Financial crime causes real harm. In Fraud, we build controls that help protect customers from scams, stolen-card fraud, account takeover and other fast-changing threats, all while keeping Monzo smooth and fair for the millions of people who use us every day.
Machine Learning is central to that work. Our ML specialists build, ship and improve models that help us spot risk, make better decisions, and keep our customers safe. We work closely with Product, Risk Partners, Engineering, Data and other disciplines to turn ambiguous fraud problems into reliable controls that make a measurable difference for customers.
We’re looking for a Machine Learning Manager to lead ML specialists across different levels of seniority in the Fraud group. You’ll report to the Senior ML Manager for the FinCrime Collective, and you’ll help the team deliver high-impact ML systems while growing a healthy, inclusive and high-performing team.
🔑 You’ll play a key role by…
- Managing, coaching and developing a team of Machine Learning specialists, helping them do the best work of their careers through regular 1:1s, clear feedback and thoughtful development plans.
- Helping the Fraud group focus ML effort on the highest-impact problems, balancing customer protection, regulatory expectations, operational impact and delivery pace.
- Partnering with PMs, Risk Partners, Engineering Managers, Data Managers and senior ML/Data colleagues to shape roadmaps, unblock delivery and make clear trade-offs.
- Creating the conditions for high-quality ML delivery: reliable model development, deployment, monitoring, governance, documentation and ownership across the full model lifecycle.
- Holding a high bar for ML excellence in Fraud, including model performance, explainability, reproducibility, observability and safe operation in production.
- Making sure ML products are owned, maintained and improved over time, rather than treated as one-off projects.
- Building a strong team culture where people give and receive useful feedback, learn from each other, and work well with cross-functional partners.
- Contributing to the wider Machine Learning and Data discipline at Monzo, including hiring, improving ways of working, and sharing patterns that help other teams move faster and more safely.
🤩 We’d love to hear from you if…
- You’ve managed Machine Learning specialists and have delivered through others and want to move further into people management.
- You have strong ML judgement and can guide teams through the full model lifecycle, from problem framing and feature/model development through to deployment, monitoring, governance and iteration.
- You’re comfortable working in ambiguous, high-impact problem spaces where there often isn’t one “right” answer.
- You can build trusted relationships with Product, Risk, Engineering, Data and senior stakeholders, and you know how to bring the right people into the right conversations early.
- You focus on outcomes over process, and can help a team prioritise work that protects customers and moves the business forward.
- You know what good looks like for production ML systems, and you can raise the bar through coaching, review, standards and pragmatic decision-making.
- You communicate clearly with technical and non-technical audiences, especially when explaining trade-offs, risks and recommendations.
- You care deeply about building inclusive teams where people with different levels of experience can grow, challenge each other, and do high-quality work sustainably.
Experience in fraud, financial crime, risk, regulated environments or customer protection would be a bonus, but it’s not the only way to be successful here. We’re most interested in your ability to lead ML work that has real-world impact.
Not ticking every box? That’s totally okay! Studies show that women and people of colour might hesitate to apply unless they meet every single requirement. At Monzo, we’re dedicated to creating a diverse and welcoming team. If you’re passionate about this role and keen to learn and grow with us, we encourage you to apply, even if you don’t have everything that's listed just yet. Drop us your application, we’d love to hear from you!
🙌 What’s in it for you
💰 £113,200 - £153,200 + Incentive Awards tied to your performance.
✈️ We can help you relocate to the UK.
✅ We can sponsor your visa.
📍This role can be based in our London office, but we're 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.
📚 £1,000 learning budget each year to use on books, training courses and conferences.
🏡 We’ll set you up to work from home; all employees are given MacBooks and for fully remote workers we’ll provide extra support for your work-from-home setup.
➕ Plus lots more! Read our full list of benefits.
🌈 The application journey has 3 key steps
- Recruiter call
- Initial interview with ML/Data leadership, focused on your people leadership, ML judgement and delivery experience.
- Loop stage, likely covering team and stakeholder leadership, technical ML judgement, and Monzo behaviours.
This process should take around 3-4 weeks - your schedule is really important to us, so we promise to be as flexible as possible!
We have some guidelines on using Artificial Intelligence (AI) to ace an application and interview at Monzo. You can read them here.
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 😊
Skills Required
- Managed Machine Learning specialists and delivered through others
- Strong ML judgement across the full model lifecycle (problem framing, feature/model development, deployment, monitoring, governance)
- Experience delivering production ML systems with focus on performance, explainability, reproducibility and observability
- Experience partnering with Product, Risk, Engineering and Data stakeholders to shape roadmaps and unblock delivery
- People management skills: coaching, regular 1:1s, feedback and development plans
- Clear communication with technical and non-technical audiences, especially explaining trade-offs and risks
- Ability to prioritise outcomes that protect customers while moving the business forward
- Experience in fraud, financial crime, risk or regulated environments
- Commitment to building inclusive teams and strong team culture
What We Do
At Monzo, we’re building a new kind of bank. One that lives on your smartphone and built for the way you live today. By solving your problems, treating you fairly and being totally transparent, we believe we can make banking better.







