About the Position

🚀 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 ❤️

📍Locations: London, Cardiff, or Remote (UK)

💰 Salary: £115,000 - £150,000 + Incentive Awards tied to your performance + Benefits ✨

About Our Machine Learning FinCrime Team

Our Financial Crime Data team consists of over 25 people across 4 data specialisms: Analytics Engineers, Data Analysts, Machine Learning Scientists, and Data Scientists. As a Lead Machine Learning Scientist, you’ll be working in a fast-moving environment, building and iterating on our financial crime defensive capabilities to ensure we keep Monzo and our customers safe.

Our financial crime team has a large impact on Monzo’s bottom line as fraud and scams are usually some of the largest cost line items in a bank's P&L. We have a major influence on the overall customer experience and it’s our duty to keep our customers safe. The work we do results in directly measurable customer or company benefit, which is incredibly satisfying.

Our Machine Learning Scientists work on a range of problems within the different financial crime areas ranging from fraud detection and prevention, transaction monitoring for different types of suspicious activity through to customer risk assessment and operational tooling.

Responsibilities

Automatically and accurately detect suspicious user behaviours while minimizing impact to genuine customers and operational costs
Adapt quickly and appropriately to changing fraud and financial crime trends, ensuring our detection systems remain performant through time

Your Day-to-Day

As a technical individual contributor, you’ll be providing technical leadership and shipping highly impactful ML-based solutions. You’ll be embedded in a cross-functional product squad, working closely with product managers, data scientists, backend engineers, and designers in an agile environment. You’ll also be a technical leader within the Machine Learning discipline, helping to steer technical work and drive up standards.

This will involve:

Working with stakeholders across the organization to identify and scope out the most impactful opportunities to tackle Financial Crime and Fraud with Machine Learning.
Leading the design and development of advanced real-time Machine Learning models, for example exploring how neural network, graph-based, and sequence-based architectures can drive improvements in detection of financial crime.
Providing technical leadership to drive up levels of technical expertise and best practice across the Machine Learning discipline, leading by example and mentoring others.
Working closely with our MLOps team to steer the ongoing development of tools to enable rapid iteration of models and optimizations of the full ML model lifecycle.

Requirements

Multiple years of experience leading the development and deployment of advanced Machine Learning models to tackle real business problems preferably in a fast-moving tech company
Experience developing and shipping deep learning, graph-based, and/or sequence-based ML architectures to production and delivering business impact
Impact-driven and excited to own the end-to-end journey that starts with a business problem and ends with your solution having a measurable impact in production
Self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
Extensive experience writing production Python code and a strong command of SQL. Comfortable using them every day, and keen to learn Go lang which is used in many of our backend microservices
Comfortable working in a team that deals with ambiguity and have experience helping your team and stakeholders resolve that ambiguity
Excited about fast-moving developments in Machine Learning and can communicate those ideas to colleagues who are not familiar with the domain
Adaptable, curious, and enjoy learning new technologies and ideas

Nice to Have

Experience working with financial crime and in regulated institutions
Commercial experience writing critical production code and working with microservices

The Interview Process

Our interview process involves 3 main stages. We promise not to ask you any brain teasers or trick questions!

30-minute recruiter call
45-minute call with hiring manager
Full Loop: ML Modelling Interview, Product & ML interview, Behavioural Interview, Leadership interview

Our average process takes around 3-4 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 but if you do have any specific questions ahead of this please contact us on [email protected]. Please also use that email to let us know if there's anything we can do to make your application process easier for you, because of disability, neurodiversity, or any other personal reason.

We Offer

✈️ We can help you relocate to the UK

✅ We can sponsor visas

📍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.

📚Learning budget of £1,000 a year for 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

About the Company

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 😊

Lead Machine Learning Scientist, FinCrime

Job description