Senior Machine Learning Scientist, FinCrime

🚀 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 ❤️

📍Cardiff, London or Remote UK  | Salary £93,000 - £120,000 + Incentive Awards tied to your performance +  benefits | Hear from the team ✨

You'll play a key role by:

This role sits as part of a multidisciplinary squad, collaborating with other Machine Learning Scientists, Data Scientists, Backend Engineers, Operations specialists, Product managers, and Risk managers. You'll play a key role by leveraging your deep experience of developing and deploying advanced Machine Learning models as to:

Automatically and accurately detect suspicious user behaviours while minimising 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.

Design machine learning solutions that scale globally.

The technical approaches you take to solve these problems will be very much in your hands and we’ll strongly encourage and support experimentation and innovation. We’ll be expecting you to justify and demonstrate effectiveness along the way, making sure the approach meets our business and customer needs.

You should apply if:

What we’re doing here at Monzo excites you!

You have a track record of deploying advanced Machine Learning models tackling real business problems with demonstrable impact, preferably in a fast moving tech company.

You're 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.

You have a passion for sharing knowledge and raising the technical bar across the team.

You have a self-starter mindset; you proactively identify the most impactful issues and opportunities and collaboratively tackle them without being told to do so.

Using advanced ML techniques to ensure Monzo’s customers money stays safe, even if their card, phone or account is compromised, sounds exciting to you.

You have extensive experience writing production Python code and a strong command of SQL. You are comfortable using them every day, and keen to learn Go lang which is used in many of our backend microservices.

You have experience developing and shipping deep learning, graph-based, and/or sequence-based ML architectures to production and delivering business impact.

You thrive working on ambiguous problems and have a track record of helping your team and stakeholders resolve that ambiguity.

You have strong communication skills and are able to explain complex technical concepts to non-technical stakeholders

You want to be involved in building a product that you and the people you know use every day, with a product mindset that prioritises customer outcomes and data-informed decisions.

You're excited about fast-moving developments in Machine Learning and can communicate those ideas to colleagues who are not familiar with the domain.

You’re adaptable, curious and enjoy learning new technologies and ideas.

Nice to haves:

Experience in supporting your team in shaping the ML strategy of your area

Experience working with financial crime, operations and in regulated institutions

Commercial experience writing critical production code and working with microservices

Experience in evaluating ML models in live environments such as through A/B tests

🙌 What’s in it for you

✈️ We’ll 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, and at times that suit you and your team.

📚 £1,000 learning budget each year to use on books, training courses and conferences.

🏡 We will set you up to work from home; all employees are given Macbooks and for fully remote workers we will provide extra support for your work-from-home setup.

➕ Plus lots more! Read our full list of benefits .

🌈 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

60 minute ML Modelling interview

60 minute Product & ML interview

60 minute behavioural 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 tech-hiring@monzo.co

#LI-REMOTE #LI-SR1

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 😊